refac: valves

examples/anthropic_manifold_pipeline.py

@@ -19,15 +19,17 @@ import requests
 
 
 class Pipeline:
+    class Valves(BaseModel):
+        ANTHROPIC_API_KEY: str = ""
+
     def __init__(self):
         self.type = "manifold"
         self.id = "anthropic"
         self.name = "anthropic/"
 
-        class Valves(BaseModel):
+        self.valves = self.Valves(
-            ANTHROPIC_API_KEY: str
+            **{"ANTHROPIC_API_KEY": os.getenv("ANTHROPIC_API_KEY")}
-
+        )
-        self.valves = Valves(**{"ANTHROPIC_API_KEY": os.getenv("ANTHROPIC_API_KEY")})
         self.client = Anthropic(api_key=self.valves.ANTHROPIC_API_KEY)
 
     def get_anthropic_models(self):

examples/cohere_manifold_pipeline.py

@@ -18,16 +18,16 @@ import requests
 
 
 class Pipeline:
+    class Valves(BaseModel):
+        COHERE_API_BASE_URL: str = "https://api.cohere.com/v1"
+        COHERE_API_KEY: str = ""
+
     def __init__(self):
         self.type = "manifold"
         self.id = "cohere"
         self.name = "cohere/"
 
-        class Valves(BaseModel):
+        self.valves = self.Valves(**{"COHERE_API_KEY": os.getenv("COHERE_API_KEY")})
-            COHERE_API_BASE_URL: str = "https://api.cohere.com/v1"
-            COHERE_API_KEY: str
-
-        self.valves = Valves(**{"COHERE_API_KEY": os.getenv("COHERE_API_KEY")})
 
         self.pipelines = self.get_cohere_models()
 

examples/conversation_turn_limit_filter.py

@@ -6,17 +6,6 @@ import time
 
 
 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"
-
-        # 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 = "conversation_turn_limit_filter_pipeline"
-        self.name = "Conversation Turn Limit Filter"
-
     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 ["*"]
@@ -31,7 +20,18 @@ class Pipeline:
         target_user_roles: List[str] = ["user"]
         max_turns: Optional[int] = None
 
-        self.valves = Valves(
+    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"
+
+        # 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 = "conversation_turn_limit_filter_pipeline"
+        self.name = "Conversation Turn Limit Filter"
+
+        self.valves = self.Valves(
             **{
                 "pipelines": os.getenv("CONVERSATION_TURN_PIPELINES", "*").split(","),
                 "max_turns": 10,

examples/detoxify_filter_pipeline.py

@@ -16,6 +16,17 @@ import os
 
 
 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 ["*"]
+        # e.g. ["llama3:latest", "gpt-3.5-turbo"]
+        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
+
     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.
@@ -28,19 +39,8 @@ class Pipeline:
         self.id = "detoxify_filter_pipeline"
         self.name = "Detoxify Filter"
 
-        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 ["*"]
-            # e.g. ["llama3:latest", "gpt-3.5-turbo"]
-            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
-
         # Initialize
-        self.valves = Valves(
+        self.valves = self.Valves(
             **{
                 "pipelines": ["*"],  # Connect to all pipelines
             }

examples/example_pipeline.py

@@ -1,8 +1,12 @@
 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.

examples/filter_pipeline.py

@@ -14,18 +14,6 @@ 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"
-
-        # 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"
-
     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 ["*"]
@@ -39,7 +27,19 @@ class Pipeline:
         # Add your custom parameters here
         pass
 
-        self.valves = Valves(**{"pipelines": ["llama3:latest"]})
+    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
 

examples/langfuse_filter_pipeline.py

@@ -18,17 +18,6 @@ from langfuse import Langfuse
 
 
 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"
-
-        # 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 = "langfuse_filter_pipeline"
-        self.name = "Langfuse Filter"
 
     class Valves(BaseModel):
         # List target pipeline ids (models) that this filter will be connected to.
@@ -46,8 +35,20 @@ class Pipeline:
         public_key: str
         host: str
 
+    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 = "langfuse_filter_pipeline"
+        self.name = "Langfuse Filter"
+
         # Initialize
-        self.valves = Valves(
+        self.valves = self.Valves(
             **{
                 "pipelines": ["*"],  # Connect to all pipelines
                 "secret_key": os.getenv("LANGFUSE_SECRET_KEY"),
@@ -94,7 +95,7 @@ class Pipeline:
             input=body,
             user_id=user["id"],
             metadata={"name": user["name"]},
-            session_id=body["chat_id"]
+            session_id=body["chat_id"],
         )
 
         print(trace.get_trace_url())

examples/libretranslate_filter_pipeline.py

@@ -8,17 +8,6 @@ from utils.main import get_last_user_message, get_last_assistant_message
 
 
 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"
-
-        # 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 = "libretranslate_filter_pipeline"
-        self.name = "LibreTranslate Filter"
 
     class Valves(BaseModel):
         # List target pipeline ids (models) that this filter will be connected to.
@@ -44,8 +33,20 @@ class Pipeline:
         source_assistant: Optional[str] = "en"
         target_assistant: Optional[str] = "es"
 
+    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 = "libretranslate_filter_pipeline"
+        self.name = "LibreTranslate Filter"
+
         # Initialize
-        self.valves = Valves(
+        self.valves = self.Valves(
             **{
                 "pipelines": ["*"],  # Connect to all pipelines
                 "libretranslate_url": os.getenv(

examples/litellm_manifold_pipeline.py

@@ -14,6 +14,10 @@ import requests
 
 
 class Pipeline:
+
+    class Valves(BaseModel):
+        LITELLM_BASE_URL: str
+
     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.
@@ -29,11 +33,8 @@ class Pipeline:
         # Optionally, you can set the name of the manifold pipeline.
         self.name = "LiteLLM: "
 
-        class Valves(BaseModel):
-            LITELLM_BASE_URL: str
-
         # Initialize rate limits
-        self.valves = Valves(**{"LITELLM_BASE_URL": "http://localhost:4001"})
+        self.valves = self.Valves(**{"LITELLM_BASE_URL": "http://localhost:4001"})
         self.pipelines = []
         pass
 

examples/litellm_subprocess_manifold_pipeline.py

@@ -21,6 +21,12 @@ import yaml
 
 
 class Pipeline:
+    class Valves(BaseModel):
+        LITELLM_CONFIG_DIR: str = "./litellm/config.yaml"
+        LITELLM_PROXY_PORT: int = 4001
+        LITELLM_PROXY_HOST: str = "127.0.0.1"
+        litellm_config: dict = {}
+
     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.
@@ -36,14 +42,8 @@ class Pipeline:
         # Optionally, you can set the name of the manifold pipeline.
         self.name = "LiteLLM: "
 
-        class Valves(BaseModel):
-            LITELLM_CONFIG_DIR: str = "./litellm/config.yaml"
-            LITELLM_PROXY_PORT: int = 4001
-            LITELLM_PROXY_HOST: str = "127.0.0.1"
-            litellm_config: dict = {}
-
         # Initialize Valves
-        self.valves = Valves(**{"LITELLM_CONFIG_DIR": f"./litellm/config.yaml"})
+        self.valves = self.Valves(**{"LITELLM_CONFIG_DIR": f"./litellm/config.yaml"})
         self.background_process = None
         pass
 

examples/ollama_manifold_pipeline.py

@@ -5,6 +5,10 @@ import requests
 
 
 class Pipeline:
+
+    class Valves(BaseModel):
+        OLLAMA_BASE_URL: str
+
     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.
@@ -20,10 +24,7 @@ class Pipeline:
         # Optionally, you can set the name of the manifold pipeline.
         self.name = "Ollama: "
 
-        class Valves(BaseModel):
+        self.valves = self.Valves(**{"OLLAMA_BASE_URL": "http://localhost:11435"})
-            OLLAMA_BASE_URL: str
-
-        self.valves = Valves(**{"OLLAMA_BASE_URL": "http://localhost:11435"})
         self.pipelines = []
         pass
 

examples/rate_limit_filter_pipeline.py

@@ -4,18 +4,8 @@ from pydantic import BaseModel
 from schemas import OpenAIChatMessage
 import time
 
+
 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"
-
-        # 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 = "rate_limit_filter_pipeline"
-        self.name = "Rate Limit Filter"
-
     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 ["*"]
@@ -32,20 +22,33 @@ class Pipeline:
         sliding_window_limit: Optional[int] = None
         sliding_window_minutes: Optional[int] = None
 
-        # Initialize rate limits
+    def __init__(self):
-        pipelines = os.getenv("RATE_LIMIT_PIPELINES", "*").split(",")
+        # Pipeline filters are only compatible with Open WebUI
-        requests_per_minute = int(os.getenv("RATE_LIMIT_REQUESTS_PER_MINUTE", 10))
+        # 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.
-        requests_per_hour = int(os.getenv("RATE_LIMIT_REQUESTS_PER_HOUR", 1000))
+        self.type = "filter"
-        sliding_window_limit = int(os.getenv("RATE_LIMIT_SLIDING_WINDOW_LIMIT", 100))
-        sliding_window_minutes = int(os.getenv("RATE_LIMIT_SLIDING_WINDOW_MINUTES", 15))
 
-        self.valves = Valves(
+        # 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 = "rate_limit_filter_pipeline"
+        self.name = "Rate Limit Filter"
+
+        # Initialize rate limits
+        self.valves = self.Valves(
             **{
-                "pipelines": pipelines,
+                "pipelines": os.getenv("RATE_LIMIT_PIPELINES", "*").split(","),
-                "requests_per_minute": requests_per_minute,
+                "requests_per_minute": int(
-                "requests_per_hour": requests_per_hour,
+                    os.getenv("RATE_LIMIT_REQUESTS_PER_MINUTE", 10)
-                "sliding_window_limit": sliding_window_limit,
+                ),
-                "sliding_window_minutes": sliding_window_minutes,
+                "requests_per_hour": int(
+                    os.getenv("RATE_LIMIT_REQUESTS_PER_HOUR", 1000)
+                ),
+                "sliding_window_limit": int(
+                    os.getenv("RATE_LIMIT_SLIDING_WINDOW_LIMIT", 100)
+                ),
+                "sliding_window_minutes": int(
+                    os.getenv("RATE_LIMIT_SLIDING_WINDOW_MINUTES", 15)
+                ),
             }
         )
 

examples/wikipedia_pipeline.py

@@ -6,6 +6,9 @@ import os
 
 
 class Pipeline:
+    class Valves(BaseModel):
+        pass
+
     def __init__(self):
         # Assign a unique identifier to the pipeline.
         # The identifier must be unique across all pipelines.
@@ -13,11 +16,8 @@ class Pipeline:
         self.id = "wiki_pipeline"
         self.name = "Wikipedia Pipeline"
 
-        class Valves(BaseModel):
-            pass
-
         # Initialize rate limits
-        self.valves = Valves(**{"OPENAI_API_KEY": os.getenv("OPENAI_API_KEY", "")})
+        self.valves = self.Valves(**{"OPENAI_API_KEY": os.getenv("OPENAI_API_KEY", "")})
 
     async def on_startup(self):
         # This function is called when the server is started.