chore

examples/scaffolds/example_pipeline_scaffold.py

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+from typing import List, Union, Generator, Iterator
+from schemas import OpenAIChatMessage
+from pydantic import BaseModel
+
+
+class Pipeline:
+    class Valves(BaseModel):
+        pass
+
+    def __init__(self):
+        # Optionally, you can set the id and name of the pipeline.
+        # Assign a unique identifier to the pipeline.
+        # The identifier must be unique across all pipelines.
+        # The identifier must be an alphanumeric string that can include underscores or hyphens. It cannot contain spaces, special characters, slashes, or backslashes.
+        self.id = "pipeline_example"
+        self.name = "Pipeline Example"
+
+        pass
+
+    async def on_startup(self):
+        # This function is called when the server is started.
+        print(f"on_startup:{__name__}")
+        pass
+
+    async def on_shutdown(self):
+        # This function is called when the server is stopped.
+        print(f"on_shutdown:{__name__}")
+        pass
+
+    async def on_valves_updated(self):
+        # This function is called when the valves are updated.
+        pass
+
+    async def inlet(self, body: dict, user: dict) -> dict:
+        # This function is called before the OpenAI API request is made. You can modify the form data before it is sent to the OpenAI API.
+        print(f"inlet:{__name__}")
+
+        print(body)
+        print(user)
+
+        return body
+
+    async def outlet(self, body: dict, user: dict) -> dict:
+        # This function is called after the OpenAI API response is completed. You can modify the messages after they are received from the OpenAI API.
+        print(f"outlet:{__name__}")
+
+        print(body)
+        print(user)
+
+        return body
+
+    def pipe(
+        self, user_message: str, model_id: str, messages: List[dict], body: dict
+    ) -> Union[str, Generator, Iterator]:
+        # This is where you can add your custom pipelines like RAG.
+        print(f"pipe:{__name__}")
+
+        print(messages)
+        print(user_message)
+        print(body)
+
+        return f"{__name__} response to: {user_message}"

examples/scaffolds/filter_pipeline_scaffold.py

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+"""
+title: Filter Pipeline
+author: open-webui
+date: 2024-05-30
+version: 1.1
+license: MIT
+description: Example of a filter pipeline that can be used to edit the form data before it is sent to the OpenAI API.
+requirements: requests
+"""
+
+from typing import List, Optional
+from pydantic import BaseModel
+from schemas import OpenAIChatMessage
+
+
+class Pipeline:
+    class Valves(BaseModel):
+        # List target pipeline ids (models) that this filter will be connected to.
+        # If you want to connect this filter to all pipelines, you can set pipelines to ["*"]
+        pipelines: List[str] = []
+
+        # Assign a priority level to the filter pipeline.
+        # The priority level determines the order in which the filter pipelines are executed.
+        # The lower the number, the higher the priority.
+        priority: int = 0
+
+        # Add your custom parameters here
+        pass
+
+    def __init__(self):
+        # Pipeline filters are only compatible with Open WebUI
+        # You can think of filter pipeline as a middleware that can be used to edit the form data before it is sent to the OpenAI API.
+        self.type = "filter"
+
+        # Optionally, you can set the id and name of the pipeline.
+        # Assign a unique identifier to the pipeline.
+        # The identifier must be unique across all pipelines.
+        # The identifier must be an alphanumeric string that can include underscores or hyphens. It cannot contain spaces, special characters, slashes, or backslashes.
+        self.id = "filter_pipeline"
+        self.name = "Filter"
+
+        self.valves = self.Valves(**{"pipelines": ["llama3:latest"]})
+
+        pass
+
+    async def on_startup(self):
+        # This function is called when the server is started.
+        print(f"on_startup:{__name__}")
+        pass
+
+    async def on_shutdown(self):
+        # This function is called when the server is stopped.
+        print(f"on_shutdown:{__name__}")
+        pass
+
+    async def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
+        # This filter is applied to the form data before it is sent to the OpenAI API.
+        print(f"inlet:{__name__}")
+
+        print(body)
+        print(user)
+
+        return body

examples/scaffolds/function_calling_scaffold.py

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+from blueprints.function_calling_blueprint import Pipeline as FunctionCallingBlueprint
+
+
+class Pipeline(FunctionCallingBlueprint):
+    class Valves(FunctionCallingBlueprint.Valves):
+        # Add your custom parameters here
+        pass
+
+    class Tools:
+        def __init__(self, pipeline) -> None:
+            self.pipeline = pipeline
+
+        # Add your custom tools using pure Python code here, make sure to add type hints
+        # Please refer to function_calling_filter_pipeline.py for an example
+        pass
+
+    def __init__(self):
+        super().__init__()
+        self.id = "my_tools_pipeline"
+        self.name = "My Tools Pipeline"
+        self.valves = self.Valves(
+            **{
+                **self.valves.model_dump(),
+                "pipelines": ["*"],  # Connect to all pipelines
+            },
+        )
+        self.tools = self.Tools(self)

examples/scaffolds/manifold_pipeline_scaffold.py

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+from typing import List, Union, Generator, Iterator
+from schemas import OpenAIChatMessage
+
+
+class Pipeline:
+    def __init__(self):
+        # You can also set the pipelines that are available in this pipeline.
+        # Set manifold to True if you want to use this pipeline as a manifold.
+        # Manifold pipelines can have multiple pipelines.
+        self.type = "manifold"
+
+        # Optionally, you can set the id and name of the pipeline.
+        # Assign a unique identifier to the pipeline.
+        # The identifier must be unique across all pipelines.
+        # The identifier must be an alphanumeric string that can include underscores or hyphens. It cannot contain spaces, special characters, slashes, or backslashes.
+        self.id = "manifold_pipeline"
+
+        # Optionally, you can set the name of the manifold pipeline.
+        self.name = "Manifold: "
+        self.pipelines = [
+            {
+                "id": "pipeline-1",  # This will turn into `manifold_pipeline.pipeline-1`
+                "name": "Pipeline 1",  # This will turn into `Manifold: Pipeline 1`
+            },
+            {
+                "id": "pipeline-2",
+                "name": "Pipeline 2",
+            },
+        ]
+        pass
+
+    async def on_startup(self):
+        # This function is called when the server is started.
+        print(f"on_startup:{__name__}")
+        pass
+
+    async def on_shutdown(self):
+        # This function is called when the server is stopped.
+        print(f"on_shutdown:{__name__}")
+        pass
+
+    def pipe(
+        self, user_message: str, model_id: str, messages: List[dict], body: dict
+    ) -> Union[str, Generator, Iterator]:
+        # This is where you can add your custom pipelines like RAG.
+        print(f"pipe:{__name__}")
+
+        print(messages)
+        print(user_message)
+        print(body)
+
+        return f"{model_id} response to: {user_message}"