import gradio as gr
import boto3, json, os

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv())

aws_access_key_id = os.environ['AWS_ACCESS_KEY_ID']
aws_secret_access_key = os.environ['AWS_SECRET_ACCESS_KEY']

bedrock_runtime = boto3.client(
    aws_access_key_id = aws_access_key_id,
    aws_secret_access_key = aws_secret_access_key,
    service_name = "bedrock-runtime",
    region_name = "us-west-2"
)

def invoke(prompt):
    #args = {
    #  "modelId": "anthropic.claude-v2",
    #  "contentType": "application/json",
    #  "accept": "*/*",
    #  "body": "{\"prompt\":\"Human: " + prompt + "\\nAssistant:\",\"max_tokens_to_sample\":300,\"temperature\":1,\"top_k\":250,\"top_p\":0.999,\"stop_sequences\":[\"\\n\\nHuman:\"],\"anthropic_version\":\"bedrock-2023-05-31\"}"
    #}
    body = json.dumps({"prompt": "Human: " + prompt + "\nAssistant:",
                       "max_tokens_to_sample": 300,
                       "temperature": 1,
                       "top_k": 250,
                       "top_p": 0.999,
                       "stop_sequences": ["\n\nHuman:"]
                      })
    print(body)
    modelId = "anthropic.claude-v2"
    accept = "application/json"
    contentType = "application/json"
    response = bedrock_runtime.invoke_model(body=body, modelId=modelId, accept=accept, contentType=contentType)
    response_body = json.loads(response.get("body").read())
    return response_body["completion"]

gr.close_all()
demo = gr.Interface(fn=invoke, 
                    inputs = [gr.Textbox(label = "Prompt", lines = 1)],
                    outputs = [gr.Textbox(label = "Result", lines = 1)],
                    title = "Generative AI - Text",
                    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")
demo.launch()