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fix: langfuse

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This commit is contained in:
Timothy J. Baek 2024-05-28 18:17:49 -07:00
parent a917293db5
commit 69be71ea4c
2 changed files with 37 additions and 105 deletions
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53
pipelines/examples/langfuse_filter_pipeline.py
View File

@ -2,6 +2,8 @@ from typing import List, Optional
from schemas import OpenAIChatMessage
import os
from pydantic import BaseModel
from langfuse import Langfuse
from langfuse.decorators import langfuse_context, observe
@ -19,32 +21,38 @@ class Pipeline:
self.id = "langfuse_filter_pipeline"
self.name = "Langfuse 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
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] = []
# List target pipelines (models) that this filter will be connected to.
# If you want to connect this filter to all pipelines, you can set pipelines to ["*"]
self.pipelines = ["*"]
# 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
self.secret_key = os.getenv("LANGFUSE_SECRET_KEY")
self.public_key = os.getenv("LANGFUSE_PUBLIC_KEY")
self.host = os.getenv("LANGFUSE_HOST")
# Valves
secret_key: str
public_key: str
host: str
self.langfuse = Langfuse(
secret_key=self.secret_key,
public_key=self.public_key,
host=self.host,
debug=True,
# Initialize
self.valves = Valves(
**{
"pipelines": ["*"], # Connect to all pipelines
"secret_key": os.getenv("LANGFUSE_SECRET_KEY"),
"public_key": os.getenv("LANGFUSE_PUBLIC_KEY"),
"host": os.getenv("LANGFUSE_HOST", "https://cloud.langfuse.com"),
}
)
self.langfuse.auth_check()
self.langfuse = None
pass
async def on_startup(self):
# This function is called when the server is started or after valves are updated.
print(f"on_startup:{__name__}")
self.set_langfuse()
pass
async def on_shutdown(self):
@ -53,6 +61,19 @@ class Pipeline:
self.langfuse.flush()
pass
async def on_valves_update(self):
self.set_langfuse()
pass
def set_langfuse(self):
self.langfuse = Langfuse(
secret_key=self.valves.secret_key,
public_key=self.valves.public_key,
host=self.valves.host,
debug=True,
)
self.langfuse.auth_check()
async def filter(self, body: dict, user: Optional[dict] = None) -> dict:
print(f"filter:{__name__}")

89
pipelines/ollama_manifold_pipeline.py
View File

@ -1,89 +0,0 @@
from typing import List, Union, Generator, Iterator
from schemas import OpenAIChatMessage
from pydantic import BaseModel
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"
# 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 = "ollama_manifold"
# Optionally, you can set the name of the manifold pipeline.
self.name = "Ollama: "
class Valves(BaseModel):
OLLAMA_BASE_URL: str
self.valves = Valves(**{"OLLAMA_BASE_URL": "http://localhost:11434"})
pass
async def on_startup(self):
# This function is called when the server is started or after valves are updated.
print(f"on_startup:{__name__}")
pass
async def on_shutdown(self):
# This function is called when the server is stopped or before valves are updated.
print(f"on_shutdown:{__name__}")
pass
def get_ollama_models(self):
if self.valves.OLLAMA_BASE_URL:
try:
r = requests.get(f"{self.valves.OLLAMA_BASE_URL}/api/tags")
models = r.json()
return [
{"id": model["model"], "name": model["name"]}
for model in models["models"]
]
except Exception as e:
print(f"Error: {e}")
return [
{
"id": self.id,
"name": "Could not fetch models from Ollama, please update the URL in the valves.",
},
]
else:
return []
# Pipelines are the models that are available in the manifold.
# It can be a list or a function that returns a list.
def pipelines(self) -> List[dict]:
return self.get_ollama_models()
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}"