Udpated

Author: naeemaa00

AWS_BedRock/Image.py

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+import boto3
+import json
+# Create a Boto3 client for Bedrock Runtime
+
+client = boto3.client('bedrock-runtime')
+
+# Specify the input data and model ID
+input_data = {
+  "modelId": "stability.stable-diffusion-xl-v0",
+  "contentType": "application/json",
+  "accept": "application/json",
+   "body": {"text_prompts":[{"text":"Sri lanka tea plantation."}],"cfg_scale":10,"seed":0,"steps":50}
+}
+
+# Invoke the model for inference
+response = client.invoke_model(contentType='application/json', body=json.dumps(input_data["body"]).encode('utf-8'), modelId=input_data['modelId'])
+
+# Retrieve the inference response
+inference_result = response['body'].read().decode('utf-8')
+
+print(inference_result)

AWS_BedRock/chat.py

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+import boto3
+import json
+import base64
+
+client = boto3.client('bedrock-runtime')
+
+# Specify the input data and model ID
+"""
+input_data = {
+  "modelId": "ai21.j2-mid-v1",
+  "contentType": "application/json",
+  "accept": "*/*",
+  "body": "{\"prompt\":\"how to cook tomato rice\",\"maxTokens\":200,\"temperature\":0.7,\"topP\":1,\"stopSequences\":[],\"countPenalty\":{\"scale\":0},\"presencePenalty\":{\"scale\":0},\"frequencyPenalty\":{\"scale\":0}}"
+}
+"""
+
+input_data = {
+  "modelId": "ai21.j2-ultra-v1",
+  "contentType": "application/json",
+  "accept": "*/*",
+  "body": {"prompt":"this is where you place your input text","maxTokens":200,"temperature":0,"topP":250,"stop_sequences":[],"countPenalty":{"scale":0},"presencePenalty":{"scale":0},"frequencyPenalty":{"scale":0}} 
+}
+
+# Invoke the model for inference
+response = client.invoke_model(contentType='application/json', body=json.dumps(input_data["body"]).encode('utf-8'), modelId=input_data['modelId'])
+
+Data = json.loads(response['body'].read().decode('utf-8'))
+print(Data)
+#Retrieve the inference response
+#print(Data['completions'][0]['data']['text'])
+#print(Data['generations'][0]['text'])
+

AWS_BedRock/playAI.py

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+import boto3
+import json
+import base64
+
+client = boto3.client('bedrock-runtime')
+
+# Specify the input data and model ID
+
+input_data = {
+  "modelId": "ai21.j2-mid-v1",
+  "contentType": "application/json",
+  "accept": "*/*",
+  "body": "{\"prompt\":\"how to cook tomato rice\",\"maxTokens\":200,\"temperature\":0.7,\"topP\":1,\"stopSequences\":[],\"countPenalty\":{\"scale\":0},\"presencePenalty\":{\"scale\":0},\"frequencyPenalty\":{\"scale\":0}}"
+}
+
+# Invoke the model for inference
+response = client.invoke_model(contentType='application/json', body=input_data['body'], modelId=input_data['modelId'])
+
+Data = json.loads(response['body'].read().decode('utf-8'))
+print(Data)
+#Retrieve the inference response
+#print(Data['completions'][0]['data']['text'])
+#print(Data['generations'][0]['text'])
+

AWS_BedRock/text.py

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+import boto3
+import json
+import base64
+
+client = boto3.client('bedrock-runtime')
+
+# Specify the input data and model ID
+input_data = {
+  "modelId": "ai21.j2-mid-v1",
+  "contentType": "application/json",
+  "accept": "*/*",
+  "body": "{\"prompt\":\"how to cook tomato rice\",\"maxTokens\":200,\"temperature\":0.7,\"topP\":1,\"stopSequences\":[],\"countPenalty\":{\"scale\":0},\"presencePenalty\":{\"scale\":0},\"frequencyPenalty\":{\"scale\":0}}"
+}
+"""
+
+input_data = {
+  "modelId": "cohere.command-text-v14",
+  "contentType": "application/json",
+  "accept": "*/*",
+  "body": "{\"prompt\":\"how to cook tomato rice\",\"max_tokens\":4000,\"temperature\":0.75,\"p\":0.01,\"k\":0,\"stop_sequences\":[],\"return_likelihoods\":\"NONE\"}"
+}
+"""
+# Invoke the model for inference
+response = client.invoke_model(contentType='application/json', body=input_data['body'], modelId=input_data['modelId'])
+
+Data = json.loads(response['body'].read().decode('utf-8'))
+
+print(Data)
+#Retrieve the inference response
+print(Data['completions'][0]['data']['text'])
+#print(Data['generations'][0]['text'])
+