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import json
import utils
import torch
import traceback
import time
import random
import bittensor as bt
from typing import Awaitable
from prompting.validator import Validator
from prompting.utils.uids import get_random_uids
from prompting.protocol import PromptingSynapse, StreamPromptingSynapse
from prompting.dendrite import DendriteResponseEvent
from .base import QueryValidatorParams, ValidatorAPI
from aiohttp.web_response import Response, StreamResponse
from deprecated import deprecated
from dataclasses import dataclass
from typing import List
from responses import TextStreamResponse
@dataclass
class ProcessedStreamResponse:
streamed_chunks: List[str]
streamed_chunks_timings: List[float]
synapse: StreamPromptingSynapse
class S1ValidatorAPI(ValidatorAPI):
def __init__(self):
self.validator = Validator()
@deprecated(
reason="This function is deprecated. Validators use stream synapse now, use get_stream_response instead."
)
async def get_response(self, params: QueryValidatorParams) -> Response:
try:
# Guess the task name of current request
task_name = utils.guess_task_name(params.messages[-1])
# Get the list of uids to query for this step.
uids = get_random_uids(
self.validator, k=params.k_miners, exclude=params.exclude or []
).tolist()
axons = [self.validator.metagraph.axons[uid] for uid in uids]
# Make calls to the network with the prompt.
bt.logging.info(f"Calling dendrite")
responses = await self.validator.dendrite(
axons=axons,
synapse=PromptingSynapse(roles=params.roles, messages=params.messages),
timeout=params.timeout,
)
bt.logging.info(f"Creating DendriteResponseEvent:\n {responses}")
# Encapsulate the responses in a response event (dataclass)
response_event = DendriteResponseEvent(
responses, torch.LongTensor(uids), params.timeout
)
# convert dict to json
response = response_event.__state_dict__()
response["completion_is_valid"] = valid = list(
map(utils.completion_is_valid, response["completions"])
)
valid_completions = [
response["completions"][i] for i, v in enumerate(valid) if v
]
response["task_name"] = task_name
response["ensemble_result"] = utils.ensemble_result(
valid_completions, task_name=task_name, prefer=params.prefer
)
bt.logging.info(f"Response:\n {response}")
return Response(
status=200,
reason="I can't believe it's not butter!",
text=json.dumps(response),
)
except Exception:
bt.logging.error(
f"Encountered in {self.__class__.__name__}:get_response:\n{traceback.format_exc()}"
)
return Response(status=500, reason="Internal error")
async def process_response(
self, response: StreamResponse, async_generator: Awaitable
) -> ProcessedStreamResponse:
"""Process a single response asynchronously."""
# Initialize chunk with a default value
chunk = None
# Initialize chunk array to accumulate streamed chunks
chunks = []
chunks_timings = []
start_time = time.time()
last_sent_index = 0
async for chunk in async_generator:
if isinstance(chunk, list):
# Chunks are currently returned in string arrays, so we need to concatenate them
concatenated_chunks = "".join(chunk)
new_data = concatenated_chunks[last_sent_index:]
if new_data:
await response.write(new_data.encode('utf-8'))
bt.logging.info(f"Received new chunk from miner: {chunk}")
last_sent_index += len(new_data)
chunks.extend(chunk)
chunks_timings.append(time.time() - start_time)
if chunk is not None and isinstance(chunk, StreamPromptingSynapse):
# Assuming the last chunk holds the last value yielded which should be a synapse with the completion filled
return ProcessedStreamResponse(
synapse=chunk,
streamed_chunks=chunks,
streamed_chunks_timings=chunks_timings
)
else:
raise ValueError("The last chunkis not a StreamPrompting synapse")
async def get_stream_response(self, params: QueryValidatorParams) -> StreamResponse:
response = StreamResponse(status=200, reason="OK")
response.headers["Content-Type"] = "application/json"
await response.prepare(params.request) # Prepare and send the headers
try:
# Guess the task name of current request
# task_name = utils.guess_task_name(params.messages[-1])
# Get the list of uids to query for this step.
uids = get_random_uids(
self.validator, k=params.k_miners, exclude=params.exclude or []
).tolist()
axons = [self.validator.metagraph.axons[uid] for uid in uids]
# Make calls to the network with the prompt.
bt.logging.info(f"Calling dendrite")
start_time = time.time()
streams_responses = await self.validator.dendrite(
axons=axons,
synapse=StreamPromptingSynapse(
roles=params.roles, messages=params.messages
),
timeout=params.timeout,
deserialize=False,
streaming=True,
)
uid_stream_dict = dict(zip(uids, streams_responses))
random_uid, random_stream = random.choice(list(uid_stream_dict.items()))
processed_response = await self.process_response(response, random_stream)
# Prepare final JSON chunk
response_data = json.dumps(TextStreamResponse(
streamed_chunks=processed_response.streamed_chunks,
streamed_chunks_timings=processed_response.streamed_chunks_timings,
uid = random_uid,
completion=processed_response.synapse.completion,
timing = time.time()- start_time
).to_dict())
# Send the final JSON as part of the stream
await response.write(json.dumps(response_data).encode("utf-8"))
except Exception as e:
bt.logging.error(
f"Encountered an error in {self.__class__.__name__}:get_stream_response:\n{traceback.format_exc()}"
)
response.set_status(500, reason="Internal error")
await response.write(json.dumps({"error": str(e)}).encode("utf-8"))
finally:
await response.write_eof() # Ensure to close the response properly
return response
async def query_validator(self, params: QueryValidatorParams) -> Response:
return await self.get_stream_response(params)
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