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import json
from typing import Optional, List, Iterator, Dict, Any
from phi.aws.api_client import AwsApiClient
from phi.llm.base import LLM
from phi.llm.message import Message
from phi.utils.log import logger
from phi.utils.timer import Timer
try:
from boto3 import session # noqa: F401
except ImportError:
logger.error("`boto3` not installed")
raise
class AwsBedrock(LLM):
name: str = "AwsBedrock"
model: str
aws_region: Optional[str] = None
aws_profile: Optional[str] = None
aws_client: Optional[AwsApiClient] = None
# -*- Request parameters
request_params: Optional[Dict[str, Any]] = None
_bedrock_client: Optional[Any] = None
_bedrock_runtime_client: Optional[Any] = None
def get_aws_region(self) -> Optional[str]:
# Priority 1: Use aws_region from model
if self.aws_region is not None:
return self.aws_region
# Priority 2: Get aws_region from env
from os import getenv
from phi.constants import AWS_REGION_ENV_VAR
aws_region_env = getenv(AWS_REGION_ENV_VAR)
if aws_region_env is not None:
self.aws_region = aws_region_env
return self.aws_region
def get_aws_profile(self) -> Optional[str]:
# Priority 1: Use aws_region from resource
if self.aws_profile is not None:
return self.aws_profile
# Priority 2: Get aws_profile from env
from os import getenv
from phi.constants import AWS_PROFILE_ENV_VAR
aws_profile_env = getenv(AWS_PROFILE_ENV_VAR)
if aws_profile_env is not None:
self.aws_profile = aws_profile_env
return self.aws_profile
def get_aws_client(self) -> AwsApiClient:
if self.aws_client is not None:
return self.aws_client
self.aws_client = AwsApiClient(aws_region=self.get_aws_region(), aws_profile=self.get_aws_profile())
return self.aws_client
@property
def bedrock_client(self):
if self._bedrock_client is not None:
return self._bedrock_client
boto3_session: session = self.get_aws_client().boto3_session
self._bedrock_client = boto3_session.client(service_name="bedrock")
return self._bedrock_client
@property
def bedrock_runtime_client(self):
if self._bedrock_runtime_client is not None:
return self._bedrock_runtime_client
boto3_session: session = self.get_aws_client().boto3_session
self._bedrock_runtime_client = boto3_session.client(service_name="bedrock-runtime")
return self._bedrock_runtime_client
@property
def api_kwargs(self) -> Dict[str, Any]:
return {}
def get_model_summaries(self) -> List[Dict[str, Any]]:
list_response: dict = self.bedrock_client.list_foundation_models()
if list_response is None or "modelSummaries" not in list_response:
return []
return list_response["modelSummaries"]
def get_model_ids(self) -> List[str]:
model_summaries: List[Dict[str, Any]] = self.get_model_summaries()
if len(model_summaries) == 0:
return []
return [model_summary["modelId"] for model_summary in model_summaries]
def get_model_details(self) -> Dict[str, Any]:
model_details: dict = self.bedrock_client.get_foundation_model(modelIdentifier=self.model)
if model_details is None or "modelDetails" not in model_details:
return {}
return model_details["modelDetails"]
def invoke(self, body: Dict[str, Any]) -> Dict[str, Any]:
response = self.bedrock_runtime_client.invoke_model(
body=json.dumps(body),
modelId=self.model,
accept="application/json",
contentType="application/json",
)
response_body = response.get("body")
if response_body is None:
return {}
return json.loads(response_body.read())
def invoke_stream(self, body: Dict[str, Any]) -> Iterator[Dict[str, Any]]:
response = self.bedrock_runtime_client.invoke_model_with_response_stream(
body=json.dumps(body),
modelId=self.model,
)
for event in response.get("body"):
chunk = event.get("chunk")
if chunk:
yield json.loads(chunk.get("bytes").decode())
def get_request_body(self, messages: List[Message]) -> Dict[str, Any]:
raise NotImplementedError("Please use a subclass of AwsBedrock")
def parse_response_message(self, response: Dict[str, Any]) -> Message:
raise NotImplementedError("Please use a subclass of AwsBedrock")
def parse_response_delta(self, response: Dict[str, Any]) -> Optional[str]:
raise NotImplementedError("Please use a subclass of AwsBedrock")
def response(self, messages: List[Message]) -> str:
logger.debug("---------- Bedrock Response Start ----------")
# -*- Log messages for debugging
for m in messages:
m.log()
response_timer = Timer()
response_timer.start()
response: Dict[str, Any] = self.invoke(body=self.get_request_body(messages))
response_timer.stop()
logger.debug(f"Time to generate response: {response_timer.elapsed:.4f}s")
# -*- Create assistant message
assistant_message = self.parse_response_message(response)
# -*- Update usage metrics
# Add response time to metrics
assistant_message.metrics["time"] = response_timer.elapsed
if "response_times" not in self.metrics:
self.metrics["response_times"] = []
self.metrics["response_times"].append(response_timer.elapsed)
# Add token usage to metrics
prompt_tokens = 0
if prompt_tokens is not None:
assistant_message.metrics["prompt_tokens"] = prompt_tokens
if "prompt_tokens" not in self.metrics:
self.metrics["prompt_tokens"] = prompt_tokens
else:
self.metrics["prompt_tokens"] += prompt_tokens
completion_tokens = 0
if completion_tokens is not None:
assistant_message.metrics["completion_tokens"] = completion_tokens
if "completion_tokens" not in self.metrics:
self.metrics["completion_tokens"] = completion_tokens
else:
self.metrics["completion_tokens"] += completion_tokens
total_tokens = prompt_tokens + completion_tokens
if total_tokens is not None:
assistant_message.metrics["total_tokens"] = total_tokens
if "total_tokens" not in self.metrics:
self.metrics["total_tokens"] = total_tokens
else:
self.metrics["total_tokens"] += total_tokens
# -*- Add assistant message to messages
messages.append(assistant_message)
assistant_message.log()
logger.debug("---------- Bedrock Response End ----------")
# -*- Return content
return assistant_message.get_content_string()
def response_stream(self, messages: List[Message]) -> Iterator[str]:
logger.debug("---------- Bedrock Response Start ----------")
assistant_message_content = ""
completion_tokens = 0
response_timer = Timer()
response_timer.start()
for delta in self.invoke_stream(body=self.get_request_body(messages)):
completion_tokens += 1
# -*- Parse response
content = self.parse_response_delta(delta)
# -*- Yield completion
if content is not None:
assistant_message_content += content
yield content
response_timer.stop()
logger.debug(f"Time to generate response: {response_timer.elapsed:.4f}s")
# -*- Create assistant message
assistant_message = Message(role="assistant")
# -*- Add content to assistant message
if assistant_message_content != "":
assistant_message.content = assistant_message_content
# -*- Update usage metrics
# Add response time to metrics
assistant_message.metrics["time"] = response_timer.elapsed
if "response_times" not in self.metrics:
self.metrics["response_times"] = []
self.metrics["response_times"].append(response_timer.elapsed)
# Add token usage to metrics
prompt_tokens = 0
assistant_message.metrics["prompt_tokens"] = prompt_tokens
if "prompt_tokens" not in self.metrics:
self.metrics["prompt_tokens"] = prompt_tokens
else:
self.metrics["prompt_tokens"] += prompt_tokens
logger.debug(f"Estimated completion tokens: {completion_tokens}")
assistant_message.metrics["completion_tokens"] = completion_tokens
if "completion_tokens" not in self.metrics:
self.metrics["completion_tokens"] = completion_tokens
else:
self.metrics["completion_tokens"] += completion_tokens
total_tokens = prompt_tokens + completion_tokens
assistant_message.metrics["total_tokens"] = total_tokens
if "total_tokens" not in self.metrics:
self.metrics["total_tokens"] = total_tokens
else:
self.metrics["total_tokens"] += total_tokens
# -*- Add assistant message to messages
messages.append(assistant_message)
assistant_message.log()
logger.debug("---------- Bedrock Response End ----------")
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