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from firebase_admin import db
import json
import boto3
class AWSClaude:
def __init__(
self, llm, env, user_id, thread_id, stream_id, app_type, other_request_params
):
self.llm = llm
self.env = env
self.other_request_params = other_request_params
# RTDB init and params
self.user_id = user_id
self.thread_id = thread_id
self.stream_id = stream_id
self.app_type = app_type
# AWS Bedrock Auth
self.session = boto3.Session(
aws_access_key_id="AKIA6GBMA2X64YV2BLZJ",
aws_secret_access_key="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",
)
if llm == "ClaudeOpus":
self.bedrock_runtime = self.session.client(
service_name="bedrock-runtime", region_name="us-west-2"
)
else:
self.bedrock_runtime = self.session.client(
service_name="bedrock-runtime", region_name="us-east-1"
)
def stream(self, response):
"""self.entry_ref.update(
{
"exec_status": True,
}
)"""
full_answer = ""
for event in response.get("body"):
try:
chunk = json.loads(event["chunk"]["bytes"])
if chunk["type"] == "content_block_delta" and "delta" in chunk.keys():
content_text = chunk["delta"]["text"]
full_answer += content_text
# print(content_text, end="")
# stream_ref = self.entry_ref.child("gpt_stream").child(
# self.stream_id
# ) # get into the child() node and use ".set"
# stream_ref.set(full_answer)
except Exception as e:
print(f"Error occurred with the steam loop {type(e).__name__}, -- {e}")
print("chunk ---", chunk)
raise e
# Set 'exec_status' back to false after execution is complete
# self.entry_ref.update(
# {
# "exec_status": False,
# }
# )
return full_answer
def llm_select(self):
if self.llm == "ClaudeOpus":
return "anthropic.claude-3-opus-20240229-v1:0"
elif self.llm == "ClaudeSonnet":
return "anthropic.claude-3-sonnet-20240229-v1:0"
elif self.llm == "ClaudeHaiku":
return "anthropic.claude-3-haiku-20240307-v1:0"
def call_claude(self):
system_prompt = '"You are an expert Equity analyst, please don\'t explicitly mention that you are Claude, or from Anthropic, or an Equity analyst in your response"'
messages = self.other_request_params.get("messages", [])
combined_messages = " ".join([str(message) for message in messages])
prompt = combined_messages
max_tokens = self.other_request_params.get("max_tokens", 3500)
temperature = self.other_request_params.get("temperature", 0)
top_p = self.other_request_params.get("top_p", 1)
body = json.dumps(
{
"system": system_prompt,
"messages": [
{"role": "user", "content": [{"type": "text", "text": prompt}]}
],
"anthropic_version": "bedrock-2023-05-31",
"max_tokens": max_tokens,
"temperature": temperature,
"top_p": top_p,
}
)
llm_id = self.llm_select()
print("llm id --- ", llm_id)
response = self.bedrock_runtime.invoke_model_with_response_stream(
body=body,
modelId=llm_id,
accept="application/json",
contentType="application/json",
)
return response
def invoke(self):
response = self.call_claude()
output = self.stream(response)
return output
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