Below is the documentation for integrating Reconify with Amazon Bedrock via a Python PIP module.
We currently support the following foundational models: Amazon Titan, AI21 Jurassic, Anthropic Claude, Cohere Command, Meta Llama 2, Mistral, and Stablity Stable Diffusion.
The first step is to create an account at app.reconify.com.
In the Reconify console, add an Application to your account. This will generate both an API_KEY and an APP_KEY which will be used in the code below to send data to Reconify.
The easiest way to get started is to use the PIP module.
pip install reconify
from reconify import reconifyBedrockRuntimeHandler
Prior to initializing the Reconify module, make sure to import Amazon's boto3 module and initialize Bedrock Runtime.
import boto3
bedrock = boto3.client('bedrock-runtime')
Configure the instance of Reconify passing the Bedrock Runtime instance along with the Reconify API_KEY and APP_KEY created above.
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = "YOUR_APP_KEY",
apiKey = "YOUR_API_KEY",
)
This is all that is needed for the basic integration. The module takes care of the rest when you call bedrock.invoke_model().
When using the Reconify module, the response body from invoke_model() will be converted from botocore.response.StreamingBody to JSON and saved in the response as "parsedBody." The StreamingBody stream will then be empty.
You can optionally turn on "debug" mode by passing in "debug = True" in the method above. This will print debug messages to the console.
You can also disable image tracking, by passing in "trackImages = False" in the method.
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = "YOUR_APP_KEY",
apiKey = "YOUR_API_KEY",
debug = True,
)
You can optionally pass in a user object or session ID to be used in the analytics reporting. The session ID will be used to group interactions together in the same session transcript.
The user object should include a unique userId, the other fields are optional.
reconifyBedrockRuntimeHandler.setUser ({
"userId": "123",
"isAuthenticated": 1,
"firstName": "Francis",
"lastName": "Smith",
"email": "",
"phone": "",
"gender": "female"
});
The session ID is a simple string.
reconifyBedrockRuntimeHandler.setSession('MySessionId');
import boto3
from reconify import reconifyBedrockRuntimeHandler
bedrock = boto3.client('bedrock-runtime')
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = 'Your_App_Key',
apiKey = 'Your_Api_Key'
)
reconifyBedrockRuntimeHandler.setUser({
"userId": "12345",
"firstName": "Jim",
"lastName": "Smith"
})
response = bedrock.invoke_model(
modelId="amazon.titan-text-express-v1",
contentType="application/json",
accept="application/json",
body = "{\"inputText\": \"Tell me a cat joke\", \"textGenerationConfig\":{\"maxTokenCount\": 512, \"temperature\": 0.2, \"topP\":0.9, \"stopSequences\":[] }}"
)
import boto3
from reconify import reconifyBedrockRuntimeHandler
bedrock = boto3.client('bedrock-runtime')
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = 'Your_App_Key',
apiKey = 'Your_Api_Key'
)
reconifyBedrockRuntimeHandler.setUser({
"userId": "12345",
"firstName": "Jim",
"lastName": "Smith"
})
response = bedrock.invoke_model(
modelId="amazon.titan-image-generator-v1",
contentType="application/json",
accept="application/json",
body="{\"textToImageParams\": {\"text\": \"a tuxedo cat\"}, \"taskType\": \"TEXT_IMAGE\", \"imageGenerationConfig\": {\"cfgScale\": 8, \"seed\": 0, \"quality\": \"standard\", \"width\": 1024, \"height\": 1024, \"numberOfImages\": 1}}"
)
import boto3
from reconify import reconifyBedrockRuntimeHandler
bedrock = boto3.client('bedrock-runtime')
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = 'Your_App_Key',
apiKey = 'Your_Api_Key'
)
reconifyBedrockRuntimeHandler.setUser({
"userId": "12345",
"firstName": "Jim",
"lastName": "Smith"
})
response = bedrock.invoke_model(
modelId="ai21.j2-mid-v1",
contentType="application/json",
accept="application/json",
body="{\"prompt\":\"Tell a cat joke.\", \"maxTokens\":200, \"temperature\":0.7, \"topP\":1, \"stopSequences\":[], \"countPenalty\":{\"scale\":0} ,\"presencePenalty\":{\"scale\":0}, \"frequencyPenalty\":{\"scale\":0}}"
)
import boto3
from reconify import reconifyBedrockRuntimeHandler
bedrock = boto3.client('bedrock-runtime')
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = 'Your_App_Key',
apiKey = 'Your_Api_Key'
)
reconifyBedrockRuntimeHandler.setUser({
"userId": "12345",
"firstName": "Jim",
"lastName": "Smith"
})
response = bedrock.invoke_model(
modelId="anthropic.claude-instant-v1",
contentType="application/json",
accept="application/json",
body = "{\"prompt\":\"\\n\\nHuman: Tell a cat joke.\\n\\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\"}"
)
import boto3
from reconify import reconifyBedrockRuntimeHandler
bedrock = boto3.client('bedrock-runtime')
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = 'Your_App_Key',
apiKey = 'Your_Api_Key'
)
reconifyBedrockRuntimeHandler.setUser({
"userId": "12345",
"firstName": "Jim",
"lastName": "Smith"
})
response = bedrock.invoke_model(
modelId="cohere.command-text-v14",
contentType="application/json",
accept="application/json",
body="{\"prompt\":\"Tell a cat joke.\", \"max_tokens\":400, \"temperature\":0.75, \"p\":0.01, \"k\":0, \"stop_sequences\":[], \"return_likelihoods\":\"NONE\"}"
)
import boto3
from reconify import reconifyBedrockRuntimeHandler
bedrock = boto3.client('bedrock-runtime')
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = 'Your_App_Key',
apiKey = 'Your_Api_Key'
)
reconifyBedrockRuntimeHandler.setUser({
"userId": "12345",
"firstName": "Jim",
"lastName": "Smith"
})
response = bedrock.invoke_model(
modelId="meta.llama2-13b-chat-v1",
contentType="application/json",
accept="application/json",
body="{\"prompt\": \"Tell me a cat joke\", \"max_gen_len\": 512, \"temperature\": 0.2, \"top_p\":0.9 }"
)
import boto3
from reconify import reconifyBedrockRuntimeHandler
bedrock = boto3.client('bedrock-runtime')
reconifyBedrockRuntimeHandler.config(bedrock,
appKey = 'Your_App_Key',
apiKey = 'Your_Api_Key'
)
reconifyBedrockRuntimeHandler.setUser({
"userId": "12345",
"firstName": "Jim",
"lastName": "Smith"
})
response = bedrock.invoke_model(
modelId="stability.stable-diffusion-xl-v0",
contentType="application/json",
accept="application/json",
body = "{\"text_prompts\":[{\"text\":\"A cat drinking boba tea\"}], \"cfg_scale\":10, \"seed\":0, \"steps\":50}"
)