Merge branch 'open-webui:main' into main

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@ -1,4 +1,13 @@
"""A manifold to integrate Google's GenAI models into Open-WebUI""" """
title: Google GenAI Manifold Pipeline
author: Marc Lopez (refactor by justinh-rahb)
date: 2024-06-06
version: 1.1
license: MIT
description: A pipeline for generating text using Google's GenAI models in Open-WebUI.
requirements: google-generativeai
environment_variables: GOOGLE_API_KEY
"""
from typing import List, Union, Iterator from typing import List, Union, Iterator
import os import os
@ -6,6 +15,7 @@ import os
from pydantic import BaseModel from pydantic import BaseModel
import google.generativeai as genai import google.generativeai as genai
from google.generativeai.types import GenerationConfig
class Pipeline: class Pipeline:
@ -72,56 +82,78 @@ class Pipeline:
def pipe( def pipe(
self, user_message: str, model_id: str, messages: List[dict], body: dict self, user_message: str, model_id: str, messages: List[dict], body: dict
) -> Union[str, Iterator]: ) -> Union[str, Iterator]:
"""The pipe function (connects open-webui to google-genai) if not self.valves.GOOGLE_API_KEY:
return "Error: GOOGLE_API_KEY is not set"
Args: try:
user_message (str): The last message input by the user genai.configure(api_key=self.valves.GOOGLE_API_KEY)
model_id (str): The model to use
messages (List[dict]): The chat history
body (dict): The raw request body in OpenAI's "chat/completions" style
Returns: if model_id.startswith("google_genai."):
str: The complete response model_id = model_id[12:]
model_id = model_id.lstrip(".")
Yields: if not model_id.startswith("gemini-"):
Iterator[str]: Yields a new message part every time it is received return f"Error: Invalid model name format: {model_id}"
"""
print(f"pipe:{__name__}") print(f"Pipe function called for model: {model_id}")
print(f"Stream mode: {body.get('stream', False)}")
system_prompt = None system_message = next((msg["content"] for msg in messages if msg["role"] == "system"), None)
google_messages = []
contents = []
for message in messages: for message in messages:
google_role = "" if message["role"] != "system":
if message["role"] == "user": if isinstance(message.get("content"), list):
google_role = "user" parts = []
elif message["role"] == "assistant": for content in message["content"]:
google_role = "model" if content["type"] == "text":
elif message["role"] == "system": parts.append({"text": content["text"]})
system_prompt = message["content"] elif content["type"] == "image_url":
continue # System promt is not inyected as a message image_url = content["image_url"]["url"]
google_messages.append( if image_url.startswith("data:image"):
genai.protos.Content( image_data = image_url.split(",")[1]
role=google_role, parts.append({"inline_data": {"mime_type": "image/jpeg", "data": image_data}})
parts=[ else:
genai.protos.Part( parts.append({"image_url": image_url})
text=message["content"], contents.append({"role": message["role"], "parts": parts})
), else:
], contents.append({
) "role": "user" if message["role"] == "user" else "model",
"parts": [{"text": message["content"]}]
})
if system_message:
contents.insert(0, {"role": "user", "parts": [{"text": f"System: {system_message}"}]})
model = genai.GenerativeModel(model_name=model_id)
generation_config = GenerationConfig(
temperature=body.get("temperature", 0.7),
top_p=body.get("top_p", 0.9),
top_k=body.get("top_k", 40),
max_output_tokens=body.get("max_tokens", 8192),
stop_sequences=body.get("stop", []),
) )
response = genai.GenerativeModel( safety_settings = body.get("safety_settings")
f"models/{model_id}", # we have to add the "models/" part again
system_instruction=system_prompt, response = model.generate_content(
).generate_content( contents,
google_messages, generation_config=generation_config,
stream=body["stream"], safety_settings=safety_settings,
stream=body.get("stream", False),
) )
if body["stream"]: if body.get("stream", False):
for chunk in response: return self.stream_response(response)
yield chunk.text else:
return ""
return response.text return response.text
except Exception as e:
print(f"Error generating content: {e}")
return f"An error occurred: {str(e)}"
def stream_response(self, response):
for chunk in response:
if chunk.text:
yield chunk.text