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import gradio as gr |
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import boto3, json, os |
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from dotenv import load_dotenv, find_dotenv |
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_ = load_dotenv(find_dotenv()) |
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aws_access_key_id = os.environ['AWS_ACCESS_KEY_ID'] |
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aws_secret_access_key = os.environ['AWS_SECRET_ACCESS_KEY'] |
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bedrock_runtime = boto3.client( |
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aws_access_key_id = aws_access_key_id, |
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aws_secret_access_key = aws_secret_access_key, |
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service_name = "bedrock-runtime", |
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region_name = "us-west-2" |
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) |
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def invoke(prompt): |
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body = json.dumps({"prompt": "Human: " + prompt + "\nAssistant:", |
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"max_tokens_to_sample": 300, |
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"temperature": 1, |
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"top_k": 250, |
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"top_p": 0.999, |
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"stop_sequences": ["\n\nHuman:"] |
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}) |
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print(body) |
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modelId = "anthropic.claude-v2" |
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accept = "application/json" |
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contentType = "application/json" |
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response = bedrock_runtime.invoke_model(body=body, modelId=modelId, accept=accept, contentType=contentType) |
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response_body = json.loads(response.get("body").read()) |
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return response_body["completion"] |
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gr.close_all() |
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demo = gr.Interface(fn=invoke, |
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inputs = [gr.Textbox(label = "Prompt", lines = 1)], |
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outputs = [gr.Textbox(label = "Result", lines = 1)], |
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title = "Generative AI - Text", |
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description = "<a href='https://www.gradio.app/'>Gradio</a> UI using <a href='https://aws.amazon.com/bedrock/'>Amazon Bedrock</a> API with Claude 2 foundation model") |
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demo.launch() |
