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https://github.com/open-webui/pipelines
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add title and some bugfix
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@ -1,3 +1,13 @@
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"""
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title: AWS Bedrock Claude Pipeline
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author: G-mario
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date: 2024-08-18
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version: 1.0
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license: MIT
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description: A pipeline for generating text and processing images using the AWS Bedrock API(By Anthropic claude).
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requirements: requests, boto3
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environment_variables: AWS_ACCESS_KEY, AWS_SECRET_KEY, AWS_REGION_NAME
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"""
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import base64
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import base64
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import json
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import json
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import logging
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import logging
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@ -6,7 +16,6 @@ from typing import List, Union, Generator, Iterator
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import boto3
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import boto3
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from schemas import OpenAIChatMessage
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from pydantic import BaseModel
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from pydantic import BaseModel
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import os
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import os
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@ -28,7 +37,7 @@ class Pipeline:
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# The identifier must be unique across all pipelines.
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# The identifier must be unique across all pipelines.
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# The identifier must be an alphanumeric string that can include underscores or hyphens. It cannot contain spaces, special characters, slashes, or backslashes.
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# The identifier must be an alphanumeric string that can include underscores or hyphens. It cannot contain spaces, special characters, slashes, or backslashes.
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# self.id = "openai_pipeline"
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# self.id = "openai_pipeline"
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self.name = "Bedrock Claude: "
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self.name = "Bedrock: "
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self.valves = self.Valves(
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self.valves = self.Valves(
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**{
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**{
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@ -79,7 +88,7 @@ class Pipeline:
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def get_models(self):
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def get_models(self):
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if self.valves.AWS_ACCESS_KEY and self.valves.AWS_SECRET_KEY:
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if self.valves.AWS_ACCESS_KEY and self.valves.AWS_SECRET_KEY:
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try:
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try:
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response = self.bedrock.list_foundation_models(byProvider='Anthropic')
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response = self.bedrock.list_foundation_models(byProvider='Anthropic', byInferenceType='ON_DEMAND')
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return [
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return [
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{
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{
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"id": model["modelId"],
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"id": model["modelId"],
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@ -131,8 +140,8 @@ class Pipeline:
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payload = {"modelId": model_id,
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payload = {"modelId": model_id,
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"messages": processed_messages,
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"messages": processed_messages,
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"system": [{'text': system_message if system_message else 'you are an intelligent ai assistant'}],
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"system": [{'text': system_message if system_message else 'you are an intelligent ai assistant'}],
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"inferenceConfig": {"temperature": 0.5},
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"inferenceConfig": {"temperature": body.get("temperature", 0.5)},
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"additionalModelRequestFields": {"top_k": 200}
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"additionalModelRequestFields": {"top_k": body.get("top_k", 200), "top_p": body.get("top_p", 0.9)}
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}
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}
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if body.get("stream", False):
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if body.get("stream", False):
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return self.stream_response(model_id, payload)
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return self.stream_response(model_id, payload)
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