mirror of
https://github.com/open-webui/functions.git
synced 2026-07-01 17:58:56 -04:00
feat: functions
This commit is contained in:
Timothy Jaeryang Baek
@@ -0,0 +1,47 @@
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"""
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title: Context Clip Filter
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author: open-webui
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author_url: https://github.com/open-webui
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funding_url: https://github.com/open-webui
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version: 0.1
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"""
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from pydantic import BaseModel, Field
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from typing import Optional
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class Filter:
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class Valves(BaseModel):
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priority: int = Field(
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default=0, description="Priority level for the filter operations."
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)
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n_last_messages: int = Field(
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default=4, description="Number of last messages to retain."
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)
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pass
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class UserValves(BaseModel):
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pass
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def __init__(self):
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self.valves = self.Valves()
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pass
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def inlet(self, body: dict, __user__: Optional[dict] = None) -> dict:
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messages = body["messages"]
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# Ensure we always keep the system prompt
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system_prompt = next(
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(message for message in messages if message.get("role") == "system"), None
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)
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if system_prompt:
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messages = [
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message for message in messages if message.get("role") != "system"
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]
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messages = messages[-self.valves.n_last_messages :]
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messages.insert(0, system_prompt)
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else: # If no system prompt, simply truncate to the last n_last_messages
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messages = messages[-self.valves.n_last_messages :]
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body["messages"] = messages
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return body
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@@ -0,0 +1,111 @@
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"""
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title: Dynamic Vision Router
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author: open-webui, atgehrhardt,
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credits to @iamg30 for v0.1.5-v0.1.7 updates
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author_url: https://github.com/open-webui
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funding_url: https://github.com/open-webui
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version: 0.1.7
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required_open_webui_version: 0.3.8
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"""
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from pydantic import BaseModel, Field
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from typing import Callable, Awaitable, Any, Optional, Literal
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import json
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from open_webui.utils.misc import get_last_user_message_item
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class Filter:
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class Valves(BaseModel):
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priority: int = Field(
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default=0,
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description="Priority level for the filter operations.",
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)
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vision_model_id: str = Field(
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default="",
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description="The identifier of the vision model to be used for processing images. Note: Compatibility is provider-specific; ollama models can only route to ollama models, and OpenAI models to OpenAI models respectively.",
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)
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skip_reroute_models: list[str] = Field(
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default_factory=list,
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description="A list of model identifiers that should not be re-routed to the chosen vision model.",
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)
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enabled_for_admins: bool = Field(
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default=False,
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description="Whether dynamic vision routing is enabled for admin users.",
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)
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enabled_for_users: bool = Field(
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default=True,
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description="Whether dynamic vision routing is enabled for regular users.",
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)
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status: bool = Field(
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default=False,
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description="A flag to enable or disable the status indicator. Set to True to enable status updates.",
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)
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pass
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def __init__(self):
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self.valves = self.Valves()
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pass
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async def inlet(
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self,
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body: dict,
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__event_emitter__: Callable[[Any], Awaitable[None]],
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__model__: Optional[dict] = None,
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__user__: Optional[dict] = None,
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) -> dict:
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if __model__["id"] in self.valves.skip_reroute_models:
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return body
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if __model__["id"] == self.valves.vision_model_id:
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return body
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if __user__ is not None:
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if __user__.get("role") == "admin" and not self.valves.enabled_for_admins:
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return body
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elif __user__.get("role") == "user" and not self.valves.enabled_for_users:
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return body
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messages = body.get("messages")
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if messages is None:
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# Handle the case where messages is None
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return body
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user_message = get_last_user_message_item(messages)
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if user_message is None:
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# Handle the case where user_message is None
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return body
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has_images = user_message.get("images") is not None
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if not has_images:
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user_message_content = user_message.get("content")
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if user_message_content is not None and isinstance(
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user_message_content, list
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):
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has_images = any(
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item.get("type") == "image_url" for item in user_message_content
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)
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if has_images:
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if self.valves.vision_model_id:
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body["model"] = self.valves.vision_model_id
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if self.valves.status:
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await __event_emitter__(
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{
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"type": "status",
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"data": {
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"description": f"Request routed to {self.valves.vision_model_id}",
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"done": True,
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},
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}
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)
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else:
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if self.valves.status:
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await __event_emitter__(
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{
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"type": "status",
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"data": {
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"description": "No vision model ID provided, routing could not be completed.",
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"done": True,
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},
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}
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)
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return body
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@@ -0,0 +1,86 @@
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"""
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title: Max Turns Filter
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author: open-webui
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author_url: https://github.com/open-webui
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funding_url: https://github.com/open-webui
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version: 0.1.1
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"""
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from pydantic import BaseModel, Field
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from typing import Optional
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class Filter:
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class Valves(BaseModel):
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priority: int = Field(
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default=0, description="Priority level for the filter operations."
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)
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max_turns_for_users: int = Field(
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default=8,
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description="Maximum allowable conversation turns for a non-admin user.",
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)
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max_turns_for_admins: int = Field(
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default=8,
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description="Maximum allowable conversation turns for an admin user.",
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)
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enabled_for_admins: bool = Field(
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default=True,
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description="Whether the max turns limit is enabled for admins.",
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)
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pass
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class UserValves(BaseModel):
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max_turns: int = Field(
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default=4, description="Maximum allowable conversation turns for a user."
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)
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pass
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def __init__(self):
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# Indicates custom file handling logic. This flag helps disengage default routines in favor of custom
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# implementations, informing the WebUI to defer file-related operations to designated methods within this class.
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# Alternatively, you can remove the files directly from the body in from the inlet hook
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# self.file_handler = True
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# Initialize 'valves' with specific configurations. Using 'Valves' instance helps encapsulate settings,
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# which ensures settings are managed cohesively and not confused with operational flags like 'file_handler'.
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self.valves = self.Valves()
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pass
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def inlet(self, body: dict, __user__: Optional[dict] = None) -> dict:
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# Modify the request body or validate it before processing by the chat completion API.
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# This function is the pre-processor for the API where various checks on the input can be performed.
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# It can also modify the request before sending it to the API.
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print(f"inlet:{__name__}")
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print(f"inlet:body:{body}")
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print(f"inlet:user:{__user__}")
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if __user__ is not None:
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messages = body.get("messages", [])
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if __user__.get("role") == "admin" and not self.valves.enabled_for_admins:
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max_turns = float("inf")
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else:
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max_turns = (
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self.valves.max_turns_for_admins
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if __user__.get("role") == "admin"
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else self.valves.max_turns_for_users
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)
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current_turns = (
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len(messages) // 2
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) # Each turn consists of a user message and an assistant response
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if current_turns >= max_turns:
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raise Exception(
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f"Conversation turn limit exceeded. The maximum turns allowed is {max_turns}."
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)
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return body
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def outlet(self, body: dict, __user__: Optional[dict] = None) -> dict:
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# Modify or analyze the response body after processing by the API.
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# This function is the post-processor for the API, which can be used to modify the response
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# or perform additional checks and analytics.
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print(f"outlet:{__name__}")
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print(f"outlet:body:{body}")
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print(f"outlet:user:{__user__}")
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return body
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@@ -0,0 +1,118 @@
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"""
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title: OpenAI Manifold Pipe
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author: open-webui
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author_url: https://github.com/open-webui
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funding_url: https://github.com/open-webui
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version: 0.1.2
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"""
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from pydantic import BaseModel, Field
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from typing import Optional, Union, Generator, Iterator
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from open_webui.utils.misc import get_last_user_message
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import os
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import requests
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class Pipe:
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class Valves(BaseModel):
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NAME_PREFIX: str = Field(
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default="OPENAI/",
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description="The prefix applied before the model names.",
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)
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OPENAI_API_BASE_URL: str = Field(
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default="https://api.openai.com/v1",
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description="The base URL for OpenAI API endpoints.",
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)
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OPENAI_API_KEY: str = Field(
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default="",
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description="Required API key to retrieve the model list.",
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)
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pass
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class UserValves(BaseModel):
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OPENAI_API_KEY: str = Field(
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default="",
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description="User-specific API key for accessing OpenAI services.",
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)
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def __init__(self):
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self.type = "manifold"
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self.valves = self.Valves()
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pass
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def pipes(self):
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if self.valves.OPENAI_API_KEY:
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try:
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headers = {}
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headers["Authorization"] = f"Bearer {self.valves.OPENAI_API_KEY}"
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headers["Content-Type"] = "application/json"
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r = requests.get(
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f"{self.valves.OPENAI_API_BASE_URL}/models", headers=headers
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)
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models = r.json()
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return [
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{
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"id": model["id"],
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"name": f'{self.valves.NAME_PREFIX}{model["name"] if "name" in model else model["id"]}',
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}
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for model in models["data"]
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if "gpt" in model["id"]
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]
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except Exception as e:
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print(f"Error: {e}")
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return [
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{
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"id": "error",
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"name": "Could not fetch models from OpenAI, please update the API Key in the valves.",
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},
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]
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else:
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return [
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{
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"id": "error",
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"name": "Global API Key not provided.",
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},
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]
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def pipe(self, body: dict, __user__: dict) -> Union[str, Generator, Iterator]:
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# This is where you can add your custom pipelines like RAG.
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print(f"pipe:{__name__}")
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print(__user__)
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user_valves = __user__.get("valves")
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if not user_valves:
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raise Exception("User Valves not configured.")
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if not user_valves.OPENAI_API_KEY:
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raise Exception("OPENAI_API_KEY not provided by the user.")
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headers = {}
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headers["Authorization"] = f"Bearer {user_valves.OPENAI_API_KEY}"
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headers["Content-Type"] = "application/json"
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model_id = body["model"][body["model"].find(".") + 1 :]
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payload = {**body, "model": model_id}
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print(payload)
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try:
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r = requests.post(
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url=f"{self.valves.OPENAI_API_BASE_URL}/chat/completions",
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json=payload,
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headers=headers,
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stream=True,
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)
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r.raise_for_status()
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if body["stream"]:
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return r.iter_lines()
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else:
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return r.json()
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except Exception as e:
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return f"Error: {e}"
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