| from application.llm.base import BaseLLM |
| from application.core.settings import settings |
| import json |
| import io |
|
|
|
|
|
|
| class LineIterator: |
| """ |
| A helper class for parsing the byte stream input. |
| |
| The output of the model will be in the following format: |
| ``` |
| b'{"outputs": [" a"]}\n' |
| b'{"outputs": [" challenging"]}\n' |
| b'{"outputs": [" problem"]}\n' |
| ... |
| ``` |
| |
| While usually each PayloadPart event from the event stream will contain a byte array |
| with a full json, this is not guaranteed and some of the json objects may be split across |
| PayloadPart events. For example: |
| ``` |
| {'PayloadPart': {'Bytes': b'{"outputs": '}} |
| {'PayloadPart': {'Bytes': b'[" problem"]}\n'}} |
| ``` |
| |
| This class accounts for this by concatenating bytes written via the 'write' function |
| and then exposing a method which will return lines (ending with a '\n' character) within |
| the buffer via the 'scan_lines' function. It maintains the position of the last read |
| position to ensure that previous bytes are not exposed again. |
| """ |
| |
| def __init__(self, stream): |
| self.byte_iterator = iter(stream) |
| self.buffer = io.BytesIO() |
| self.read_pos = 0 |
|
|
| def __iter__(self): |
| return self |
|
|
| def __next__(self): |
| while True: |
| self.buffer.seek(self.read_pos) |
| line = self.buffer.readline() |
| if line and line[-1] == ord('\n'): |
| self.read_pos += len(line) |
| return line[:-1] |
| try: |
| chunk = next(self.byte_iterator) |
| except StopIteration: |
| if self.read_pos < self.buffer.getbuffer().nbytes: |
| continue |
| raise |
| if 'PayloadPart' not in chunk: |
| print('Unknown event type:' + chunk) |
| continue |
| self.buffer.seek(0, io.SEEK_END) |
| self.buffer.write(chunk['PayloadPart']['Bytes']) |
|
|
| class SagemakerAPILLM(BaseLLM): |
|
|
| def __init__(self, *args, **kwargs): |
| import boto3 |
| runtime = boto3.client( |
| 'runtime.sagemaker', |
| aws_access_key_id='xxx', |
| aws_secret_access_key='xxx', |
| region_name='us-west-2' |
| ) |
|
|
| |
| self.endpoint = settings.SAGEMAKER_ENDPOINT |
| self.runtime = runtime |
|
|
|
|
| def gen(self, model, engine, messages, stream=False, **kwargs): |
| context = messages[0]['content'] |
| user_question = messages[-1]['content'] |
| prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n" |
| |
|
|
| |
| payload = { |
| "inputs": prompt, |
| "stream": False, |
| "parameters": { |
| "do_sample": True, |
| "temperature": 0.1, |
| "max_new_tokens": 30, |
| "repetition_penalty": 1.03, |
| "stop": ["</s>", "###"] |
| } |
| } |
| body_bytes = json.dumps(payload).encode('utf-8') |
|
|
| |
| response = self.runtime.invoke_endpoint(EndpointName=self.endpoint, |
| ContentType='application/json', |
| Body=body_bytes) |
| result = json.loads(response['Body'].read().decode()) |
| import sys |
| print(result[0]['generated_text'], file=sys.stderr) |
| return result[0]['generated_text'][len(prompt):] |
|
|
| def gen_stream(self, model, engine, messages, stream=True, **kwargs): |
| context = messages[0]['content'] |
| user_question = messages[-1]['content'] |
| prompt = f"### Instruction \n {user_question} \n ### Context \n {context} \n ### Answer \n" |
| |
|
|
| |
| payload = { |
| "inputs": prompt, |
| "stream": True, |
| "parameters": { |
| "do_sample": True, |
| "temperature": 0.1, |
| "max_new_tokens": 512, |
| "repetition_penalty": 1.03, |
| "stop": ["</s>", "###"] |
| } |
| } |
| body_bytes = json.dumps(payload).encode('utf-8') |
|
|
| |
| response = self.runtime.invoke_endpoint_with_response_stream(EndpointName=self.endpoint, |
| ContentType='application/json', |
| Body=body_bytes) |
| |
| event_stream = response['Body'] |
| start_json = b'{' |
| for line in LineIterator(event_stream): |
| if line != b'' and start_json in line: |
| |
| data = json.loads(line[line.find(start_json):].decode('utf-8')) |
| if data['token']['text'] not in ["</s>", "###"]: |
| print(data['token']['text'],end='') |
| yield data['token']['text'] |