refac: valves -> filters

main.py

@@ -13,7 +13,7 @@ import json
 import uuid
 
 from utils import get_last_user_message, stream_message_template
-from schemas import ValveForm, OpenAIChatCompletionForm
+from schemas import FilterForm, OpenAIChatCompletionForm
 
 import os
 import importlib.util
@@ -61,30 +61,43 @@ def on_startup():
 
         PIPELINE_MODULES[pipeline_id] = pipeline
 
-        if hasattr(pipeline, "manifold") and pipeline.manifold:
-            for p in pipeline.pipelines:
-                manifold_pipeline_id = f'{pipeline_id}.{p["id"]}'
+        if hasattr(pipeline, "type"):
+            if pipeline.type == "manifold":
+                for p in pipeline.pipelines:
+                    manifold_pipeline_id = f'{pipeline_id}.{p["id"]}'
 
-                manifold_pipeline_name = p["name"]
-                if hasattr(pipeline, "name"):
-                    manifold_pipeline_name = f"{pipeline.name}{manifold_pipeline_name}"
+                    manifold_pipeline_name = p["name"]
+                    if hasattr(pipeline, "name"):
+                        manifold_pipeline_name = (
+                            f"{pipeline.name}{manifold_pipeline_name}"
+                        )
 
-                PIPELINES[manifold_pipeline_id] = {
+                    PIPELINES[manifold_pipeline_id] = {
+                        "module": pipeline_id,
+                        "id": manifold_pipeline_id,
+                        "name": manifold_pipeline_name,
+                        "manifold": True,
+                    }
+            if pipeline.type == "filter":
+                PIPELINES[pipeline_id] = {
                     "module": pipeline_id,
-                    "id": manifold_pipeline_id,
-                    "name": manifold_pipeline_name,
-                    "manifold": True,
+                    "id": pipeline_id,
+                    "name": (
+                        pipeline.name if hasattr(pipeline, "name") else pipeline_id
+                    ),
+                    "filter": True,
+                    "pipelines": (
+                        pipeline.pipelines if hasattr(pipeline, "pipelines") else []
+                    ),
+                    "priority": (
+                        pipeline.priority if hasattr(pipeline, "priority") else 0
+                    ),
                 }
         else:
-            PIPELINES[loaded_module.__name__] = {
+            PIPELINES[pipeline_id] = {
                 "module": pipeline_id,
                 "id": pipeline_id,
                 "name": (pipeline.name if hasattr(pipeline, "name") else pipeline_id),
-                "valve": hasattr(pipeline, "valve"),
-                "pipelines": (
-                    pipeline.pipelines if hasattr(pipeline, "pipelines") else []
-                ),
-                "priority": pipeline.priority if hasattr(pipeline, "priority") else 0,
             }
 
 
@@ -147,30 +160,38 @@ async def get_models():
                 "object": "model",
                 "created": int(time.time()),
                 "owned_by": "openai",
-                "pipeline": {
-                    "type": "pipeline" if not pipeline.get("valve") else "valve",
-                    "pipelines": pipeline.get("pipelines", []),
-                    "priority": pipeline.get("priority", 0),
-                },
+                **(
+                    {
+                        "pipeline": {
+                            "type": (
+                                "pipeline" if not pipeline.get("filter") else "filter"
+                            ),
+                            "pipelines": pipeline.get("pipelines", []),
+                            "priority": pipeline.get("priority", 0),
+                        }
+                    }
+                    if pipeline.get("filter", False)
+                    else {}
+                ),
             }
             for pipeline in PIPELINES.values()
         ]
     }
 
 
-@app.post("/valve")
-@app.post("/v1/valve")
-async def valve(form_data: ValveForm):
+@app.post("/filter")
+@app.post("/v1/filter")
+async def filter(form_data: FilterForm):
     if form_data.model not in app.state.PIPELINES or not app.state.PIPELINES[
         form_data.model
-    ].get("valve", False):
+    ].get("filter", False):
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND,
-            detail=f"Valve {form_data.model} not found",
+            detail=f"filter {form_data.model} not found",
         )
 
     pipeline = PIPELINE_MODULES[form_data.model]
-    return await pipeline.control_valve(form_data.body, form_data.user)
+    return await pipeline.filter(form_data.body, form_data.user)
 
 
 @app.post("/chat/completions")
@@ -181,7 +202,7 @@ async def generate_openai_chat_completion(form_data: OpenAIChatCompletionForm):
 
     if form_data.model not in app.state.PIPELINES or app.state.PIPELINES[
         form_data.model
-    ].get("valve", False):
+    ].get("filter", False):
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND,
             detail=f"Pipeline {form_data.model} not found",
@@ -197,14 +218,14 @@ async def generate_openai_chat_completion(form_data: OpenAIChatCompletionForm):
 
         if pipeline.get("manifold", False):
             manifold_id, pipeline_id = pipeline_id.split(".", 1)
-            get_response = PIPELINE_MODULES[manifold_id].get_response
+            pipe = PIPELINE_MODULES[manifold_id].pipe
         else:
-            get_response = PIPELINE_MODULES[pipeline_id].get_response
+            pipe = PIPELINE_MODULES[pipeline_id].pipe
 
         if form_data.stream:
 
             def stream_content():
-                res = get_response(
+                res = pipe(
                     user_message=user_message,
                     model_id=pipeline_id,
                     messages=messages,
@@ -258,7 +279,7 @@ async def generate_openai_chat_completion(form_data: OpenAIChatCompletionForm):
 
             return StreamingResponse(stream_content(), media_type="text/event-stream")
         else:
-            res = get_response(
+            res = pipe(
                 user_message=user_message,
                 model_id=pipeline_id,
                 messages=messages,

pipelines/examples/applescript_pipeline.py

@@ -24,11 +24,11 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         OLLAMA_BASE_URL = "http://localhost:11434"
         MODEL = "llama3"

pipelines/examples/azure_openai_pipeline.py

@@ -20,11 +20,11 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         print(messages)
         print(user_message)

pipelines/examples/filter_pipeline.py

@@ -4,18 +4,19 @@ from schemas import OpenAIChatMessage
 
 class Pipeline:
     def __init__(self):
-        # Pipeline valves are only compatible with Open WebUI
-        # You can think of valve pipeline as a middleware that can be used to edit the form data before it is sent to the OpenAI API.
-        self.valve = True
-        self.id = "valve_pipeline"
-        self.name = "Valve"
+        # 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"
 
-        # Assign a priority level to the valve pipeline.
-        # The priority level determines the order in which the valve pipelines are executed.
+        self.id = "filter_pipeline"
+        self.name = "Filter"
+
+        # 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.
         self.priority = 0
 
-        # List target pipelines (models) that this valve will be connected to.
+        # List target pipelines (models) that this filter will be connected to.
         self.pipelines = [
             {"id": "llama3:latest"},
         ]
@@ -31,8 +32,8 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    async def control_valve(self, body: dict, user: Optional[dict] = None) -> dict:
-        print(f"get_response:{__name__}")
+    async def filter(self, body: dict, user: Optional[dict] = None) -> dict:
+        print(f"pipe:{__name__}")
 
         print(body)
         print(user)

pipelines/examples/haystack_pipeline.py

@@ -78,7 +78,7 @@ class Pipeline:
         # This function is called when the server is stopped.
         pass
 
-    def get_response(
+    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 RAG pipeline.

pipelines/examples/llama_cpp_pipeline.py

@@ -29,11 +29,11 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         print(messages)
         print(user_message)

pipelines/examples/llamaindex_ollama_github_pipeline.py

@@ -69,7 +69,7 @@ class Pipeline:
         # This function is called when the server is stopped.
         pass
 
-    def get_response(
+    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 RAG pipeline.

pipelines/examples/llamaindex_ollama_pipeline.py

@@ -29,7 +29,7 @@ class Pipeline:
         # This function is called when the server is stopped.
         pass
 
-    def get_response(
+    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 RAG pipeline.

pipelines/examples/llamaindex_pipeline.py

@@ -24,7 +24,7 @@ class Pipeline:
         # This function is called when the server is stopped.
         pass
 
-    def get_response(
+    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 RAG pipeline.

pipelines/examples/manifold_pipeline.py

@@ -7,7 +7,7 @@ class Pipeline:
         # 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.manifold = True
+        self.type = "manifold"
 
         self.id = "manifold_pipeline"
         # Optionally, you can set the name of the manifold pipeline.
@@ -34,11 +34,11 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         print(messages)
         print(user_message)

pipelines/examples/mlx_pipeline.py

@@ -17,6 +17,7 @@ import subprocess
 import logging
 from huggingface_hub import login
 
+
 class Pipeline:
     def __init__(self):
         self.id = "mlx_pipeline"
@@ -24,7 +25,9 @@ class Pipeline:
         self.host = os.getenv("MLX_HOST", "localhost")
         self.port = os.getenv("MLX_PORT", "8080")
         self.model = os.getenv("MLX_MODEL", "mistralai/Mistral-7B-Instruct-v0.2")
-        self.stop_sequence = os.getenv("MLX_STOP", "[INST]").split(",")  # Default stop sequence is [INST]
+        self.stop_sequence = os.getenv("MLX_STOP", "[INST]").split(
+            ","
+        )  # Default stop sequence is [INST]
         self.subprocess = os.getenv("MLX_SUBPROCESS", "true").lower() == "true"
         self.huggingface_token = os.getenv("HUGGINGFACE_TOKEN", None)
 
@@ -43,8 +46,9 @@ class Pipeline:
 
     def find_free_port(self):
         import socket
+
         s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
-        s.bind(('', 0))
+        s.bind(("", 0))
         port = s.getsockname()[1]
         s.close()
         return port
@@ -53,14 +57,14 @@ class Pipeline:
         logging.info(f"on_startup:{__name__}")
 
     async def on_shutdown(self):
-        if self.subprocess and hasattr(self, 'server_process'):
+        if self.subprocess and hasattr(self, "server_process"):
             self.server_process.terminate()
             logging.info(f"Terminated MLX server on port {self.port}")
 
-    def get_response(
+    def pipe(
         self, user_message: str, model_id: str, messages: List[dict], body: dict
     ) -> Union[str, Generator, Iterator]:
-        logging.info(f"get_response:{__name__}")
+        logging.info(f"pipe:{__name__}")
 
         url = f"http://{self.host}:{self.port}/v1/chat/completions"
         headers = {"Content-Type": "application/json"}
@@ -84,11 +88,13 @@ class Pipeline:
             "temperature": temperature,
             "repetition_penalty": repeat_penalty,
             "stop": self.stop_sequence,
-            "stream": body.get("stream", False)
+            "stream": body.get("stream", False),
         }
 
         try:
-            r = requests.post(url, headers=headers, json=payload, stream=body.get("stream", False))
+            r = requests.post(
+                url, headers=headers, json=payload, stream=body.get("stream", False)
+            )
             r.raise_for_status()
 
             if body.get("stream", False):

pipelines/examples/ollama_manifold_pipeline.py

@@ -8,7 +8,7 @@ class Pipeline:
         # 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.manifold = True
+        self.type = "manifold"
         self.id = "ollama_manifold"
         # Optionally, you can set the name of the manifold pipeline.
         self.name = "Ollama: "
@@ -35,7 +35,7 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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.'

pipelines/examples/ollama_pipeline.py

@@ -20,11 +20,11 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         OLLAMA_BASE_URL = "http://localhost:11434"
         MODEL = "llama3"

pipelines/examples/openai_pipeline.py

@@ -20,11 +20,11 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         print(messages)
         print(user_message)

pipelines/examples/pipeline_example.py

@@ -19,11 +19,11 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         print(messages)
         print(user_message)

pipelines/examples/python_code_pipeline.py

@@ -30,11 +30,11 @@ class Pipeline:
         except subprocess.CalledProcessError as e:
             return e.output.strip(), e.returncode
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         print(messages)
         print(user_message)

pipelines/examples/valve_pipeline.py

@@ -1,37 +0,0 @@
-from typing import List, Union, Generator, Iterator
-from schemas import OpenAIChatMessage
-
-
-class Pipeline:
-    def __init__(self):
-        # Pipeline valves are only compatible with Open WebUI
-        # You can think of valve pipeline as a middleware that can be used to edit the form data before it is sent to the OpenAI API.
-        self.valve = True
-        self.id = "valve_pipeline"
-        self.name = "Valve"
-
-        # Assign a priority level to the valve pipeline.
-        # The priority level determines the order in which the valve pipelines are executed.
-        # The lower the number, the higher the priority.
-        self.priority = 0
-
-        # List target pipelines (models) that this valve will be connected to.
-        self.pipelines = [
-            {"id": "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 control_valve(self, body: dict) -> dict:
-        print(f"get_response:{__name__}")
-        print(body)
-        return body

pipelines/filter_pipeline.py

@@ -0,0 +1,41 @@
+from typing import List, Optional
+from schemas import OpenAIChatMessage
+
+
+class Pipeline:
+    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"
+
+        self.id = "filter_pipeline"
+        self.name = "Filter"
+
+        # 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.
+        self.priority = 0
+
+        # List target pipelines (models) that this filter will be connected to.
+        self.pipelines = [
+            {"id": "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 filter(self, body: dict, user: Optional[dict] = None) -> dict:
+        print(f"pipe:{__name__}")
+
+        print(body)
+        print(user)
+
+        return body

pipelines/ollama_manifold_pipeline.py

@@ -0,0 +1,63 @@
+from typing import List, Union, Generator, Iterator
+from schemas import OpenAIChatMessage
+import requests
+
+
+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"
+        self.id = "ollama_manifold"
+        # Optionally, you can set the name of the manifold pipeline.
+        self.name = "Ollama: "
+
+        self.OLLAMA_BASE_URL = "http://localhost:11434"
+        self.pipelines = self.get_ollama_models()
+        pass
+
+    def get_ollama_models(self):
+        r = requests.get(f"{self.OLLAMA_BASE_URL}/api/tags")
+        models = r.json()
+
+        return [
+            {"id": model["model"], "name": model["name"]} for model in models["models"]
+        ]
+
+    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.'
+
+        if "user" in body:
+            print("######################################")
+            print(f'# User: {body["user"]["name"]} ({body["user"]["id"]})')
+            print(f"# Message: {user_message}")
+            print("######################################")
+
+        try:
+            r = requests.post(
+                url=f"{self.OLLAMA_BASE_URL}/v1/chat/completions",
+                json={**body, "model": model_id},
+                stream=True,
+            )
+
+            r.raise_for_status()
+
+            if body["stream"]:
+                return r.iter_lines()
+            else:
+                return r.json()
+        except Exception as e:
+            return f"Error: {e}"

pipelines/ollama_pipeline.py

@@ -20,11 +20,11 @@ class Pipeline:
         print(f"on_shutdown:{__name__}")
         pass
 
-    def get_response(
+    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"get_response:{__name__}")
+        print(f"pipe:{__name__}")
 
         OLLAMA_BASE_URL = "http://localhost:11434"
         MODEL = "llama3"

schemas.py

@@ -17,7 +17,7 @@ class OpenAIChatCompletionForm(BaseModel):
     model_config = ConfigDict(extra="allow")
 
 
-class ValveForm(BaseModel):
+class FilterForm(BaseModel):
     model: str
     body: dict
     user: Optional[dict] = None