Olas-predict-dataset / scripts /mech_request_utils.py
Skanislav
fix: merge files cold start
d7ec263
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
#
# Copyright 2024 Valory AG
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# ------------------------------------------------------------------------------
"""Script for retrieving mech requests and their delivers."""
import json
import time
import pickle
from random import uniform
from typing import Any, Dict, Tuple
import requests
from gql import Client, gql
from gql.transport.requests import RequestsHTTPTransport
from tools import (
GET_CONTENTS_BATCH_SIZE,
IRRELEVANT_TOOLS,
create_session,
request,
)
from tqdm import tqdm
from web3_utils import (
FPMM_QS_CREATOR,
FPMM_PEARL_CREATOR,
IPFS_POLL_INTERVAL,
SUBGRAPH_POLL_INTERVAL,
)
from concurrent.futures import ThreadPoolExecutor, as_completed
from utils import (
ROOT_DIR,
TMP_DIR,
JSON_DATA_DIR,
MECH_SUBGRAPH_URL,
SUBGRAPH_API_KEY,
IPFS_ADDRESS,
save_json_file,
)
NUM_WORKERS = 30
BLOCKS_CHUNK_SIZE = 10000
TEXT_ALIGNMENT = 30
MINIMUM_WRITE_FILE_DELAY_SECONDS = 20
MECH_FROM_BLOCK_RANGE = 50000
MECH_SANDBOX_SUBGRAPH = (
"https://api.studio.thegraph.com/query/81754/mech-sandbox/version/latest"
)
last_write_time = 0.0
REQUESTS_QUERY_FILTER = """
query requests_query($sender_not_in: [Bytes!], $id_gt: Bytes, $blockNumber_gte: BigInt, $blockNumber_lte: BigInt) {
requests(where: {sender_not_in: $sender_not_in, id_gt: $id_gt, blockNumber_gte: $blockNumber_gte, blockNumber_lte: $blockNumber_lte}, orderBy: id, first: 1000) {
blockNumber
blockTimestamp
id
ipfsHash
requestId
sender
transactionHash
}
}
"""
REQUESTS_BY_MECH_QUERY_FILTER = """
query requests_query($sender_not_in: [Bytes!], $id_gt: Bytes, $blockNumber_gte: BigInt, $blockNumber_lte: BigInt) {
requests(where: {sender_not_in: $sender_not_in, id_gt: $id_gt, blockNumber_gte: $blockNumber_gte, blockNumber_lte: $blockNumber_lte}, orderBy: id, first: 1000) {
blockNumber
blockTimestamp
id
ipfsHash
requestId
sender
mech
transactionHash
}
}
"""
DELIVERS_QUERY_NO_FILTER = """
query delivers_query($id_gt: Bytes, $blockNumber_gte: BigInt, $blockNumber_lte: BigInt) {
delivers(where: {id_gt: $id_gt, blockNumber_gte: $blockNumber_gte, blockNumber_lte: $blockNumber_lte}, orderBy: id, first: 1000) {
blockNumber
blockTimestamp
id
ipfsHash
requestId
sender
transactionHash
}
}
"""
DELIVERS_BY_MECH_QUERY_NO_FILTER = """
query delivers_query($id_gt: Bytes, $blockNumber_gte: BigInt, $blockNumber_lte: BigInt) {
delivers(where: {id_gt: $id_gt, blockNumber_gte: $blockNumber_gte, blockNumber_lte: $blockNumber_lte}, orderBy: id, first: 1000) {
blockNumber
blockTimestamp
id
ipfsHash
requestId
sender
mech
transactionHash
}
}
"""
DELIVERS_QUERY = """
query delivers_query($requestId: BigInt, $blockNumber_gte: BigInt, $blockNumber_lte: BigInt) {
delivers(where: {requestId: $requestId, blockNumber_gte: $blockNumber_gte, blockNumber_lte: $blockNumber_lte}, orderBy: blockNumber, first: 1000) {
blockNumber
blockTimestamp
id
ipfsHash
requestId
sender
transactionHash
}
}
"""
DELIVERS_BY_MECH_QUERY = """
query delivers_query($requestId: BigInt, $blockNumber_gte: BigInt, $blockNumber_lte: BigInt) {
delivers(where: {requestId: $requestId, blockNumber_gte: $blockNumber_gte, blockNumber_lte: $blockNumber_lte}, orderBy: blockNumber, first: 1000) {
blockNumber
blockTimestamp
id
ipfsHash
requestId
sender
mech
transactionHash
}
}
"""
MISSING_DELIVERS_QUERY = """
query delivers_query($requestId: BigInt, $blockNumber_gte: BigInt, $blockNumber_lte: BigInt) {
delivers(where: {requestId: $requestId, blockNumber_gte: $blockNumber_gte, blockNumber_lte: $blockNumber_lte}, orderBy: blockNumber, first: 1000) {
blockNumber
blockTimestamp
id
ipfsHash
requestId
sender
transactionHash
}
}
"""
MISSING_BY_MECH_DELIVERS_QUERY = """
query delivers_query($requestId: BigInt, $blockNumber_gte: BigInt, $blockNumber_lte: BigInt) {
delivers(where: {requestId: $requestId, blockNumber_gte: $blockNumber_gte, blockNumber_lte: $blockNumber_lte}, orderBy: blockNumber, first: 1000) {
blockNumber
blockTimestamp
id
ipfsHash
requestId
sender
mech
transactionHash
}
}
"""
def collect_all_mech_requests(
from_block: int, to_block: int, filename: str, mech_sandbox: bool = False
) -> Tuple:
print(f"Fetching all mech requests from {from_block} to {to_block}")
mech_requests = {}
duplicated_reqIds = []
if mech_sandbox:
mech_subgraph_url = MECH_SANDBOX_SUBGRAPH
request_query = REQUESTS_BY_MECH_QUERY_FILTER
else:
mech_subgraph_url = MECH_SUBGRAPH_URL.substitute(
subgraph_api_key=SUBGRAPH_API_KEY
)
request_query = REQUESTS_QUERY_FILTER
transport = RequestsHTTPTransport(url=mech_subgraph_url)
client = Client(transport=transport, fetch_schema_from_transport=False)
id_gt = "0x00"
nr_errors = 0
last_id_gt = 0
while True:
variables = {
"sender_not_in": [FPMM_QS_CREATOR, FPMM_PEARL_CREATOR],
"id_gt": id_gt,
"blockNumber_gte": str(from_block), # str
"blockNumber_lte": str(to_block), # str
}
try:
response = fetch_with_retry(client, request_query, variables)
items = response.get("requests", [])
if not items:
break
for mech_request in items:
if mech_request["id"] not in mech_requests:
mech_requests[mech_request["id"]] = mech_request
else:
duplicated_reqIds.append(mech_request["id"])
except Exception as e:
# counter for errors
nr_errors += 1
print(f"Error while getting the response: {e}")
id_gt = items[-1]["id"]
time.sleep(SUBGRAPH_POLL_INTERVAL)
print(f"New execution for id_gt = {id_gt}")
if len(duplicated_reqIds) > 0:
print(f"Number of duplicated req Ids = {len(duplicated_reqIds)}")
save_json_file(mech_requests, filename)
print(f"Number of requests = {len(mech_requests)}")
print(f"Number of duplicated req Ids = {len(duplicated_reqIds)}")
save_json_file(mech_requests, filename)
return mech_requests, duplicated_reqIds, nr_errors
def fetch_with_retry(client, query, variables, max_retries=5):
for attempt in range(max_retries):
try:
return client.execute(gql(query), variable_values=variables)
except Exception as e:
print(f"Error while getting the response: {e}")
if attempt == max_retries - 1:
raise e
wait_time = (2**attempt) + uniform(0, 1) # exponential backoff with jitter
time.sleep(wait_time)
def collect_all_mech_delivers(
from_block: int, to_block: int, filename: str, mech_sandbox: bool = False
) -> Tuple:
print(f"Fetching all mech delivers from {from_block} to {to_block}")
mech_delivers = {}
duplicated_requestIds = []
if mech_sandbox:
mech_subgraph_url = MECH_SANDBOX_SUBGRAPH
deliver_query = DELIVERS_BY_MECH_QUERY_NO_FILTER
else:
mech_subgraph_url = MECH_SUBGRAPH_URL.substitute(
subgraph_api_key=SUBGRAPH_API_KEY
)
deliver_query = DELIVERS_QUERY_NO_FILTER
transport = RequestsHTTPTransport(url=mech_subgraph_url)
client = Client(transport=transport, fetch_schema_from_transport=False)
to_block = (
to_block + MECH_FROM_BLOCK_RANGE
) # there is a delay between deliver and request
id_gt = ""
nr_errors = 0
while True:
variables = {
"id_gt": id_gt,
"blockNumber_gte": str(from_block), # str
"blockNumber_lte": str(to_block), # str
}
try:
response = fetch_with_retry(client, deliver_query, variables)
items = response.get("delivers", [])
if not items:
break
for mech_deliver in items:
if mech_deliver["requestId"] not in mech_delivers:
mech_delivers[mech_deliver["requestId"]] = [mech_deliver]
else:
duplicated_requestIds.append(mech_deliver["requestId"])
# we will handle the duplicated later
except Exception as e:
# counter for errors
nr_errors += 1
print(f"Error while getting the response: {e}")
# return None, None
id_gt = items[-1]["id"]
time.sleep(SUBGRAPH_POLL_INTERVAL)
print(f"New execution for id_gt = {id_gt}")
if len(duplicated_requestIds) > 0:
print(f"Number of duplicated request id = {len(duplicated_requestIds)}")
save_json_file(mech_delivers, filename)
print(f"Number of delivers = {len(mech_delivers)}")
print(f"Number of duplicated request id = {len(duplicated_requestIds)}")
save_json_file(mech_delivers, filename)
return mech_delivers, duplicated_requestIds, nr_errors
def collect_missing_delivers(
request_id: int, block_number: int, mech_sandbox: bool = False
) -> Dict[str, Any]:
to_block = (
block_number + MECH_FROM_BLOCK_RANGE
) # there is a delay between deliver and request
print(f"Fetching all missing delivers from {block_number} to {to_block}")
mech_delivers = {}
if mech_sandbox:
mech_subgraph_url = MECH_SANDBOX_SUBGRAPH
missing_query = MISSING_BY_MECH_DELIVERS_QUERY
else:
mech_subgraph_url = MECH_SUBGRAPH_URL.substitute(
subgraph_api_key=SUBGRAPH_API_KEY
)
missing_query = MISSING_DELIVERS_QUERY
transport = RequestsHTTPTransport(url=mech_subgraph_url)
client = Client(transport=transport, fetch_schema_from_transport=False)
variables = {
"requestId": request_id,
"blockNumber_gte": str(block_number), # str
"blockNumber_lte": str(to_block), # str
}
try:
response = fetch_with_retry(client, missing_query, variables)
items = response.get("delivers", [])
# If the user sends requests with the same values (tool, prompt, nonce) it
# will generate the same requestId. Therefore, multiple items can be retrieved
# at this point. We assume the most likely deliver to this request is the
# one with the closest blockNumber among all delivers with the same requestId.
if items:
return items[0]
except Exception as e:
print(f"Error while getting the response: {e}")
# TODO count how many mech requests without a deliver do we have
return mech_delivers
def populate_requests_ipfs_contents(
session: requests.Session, mech_requests: Dict[str, Any], keys_to_traverse: list
) -> dict:
updated_dict = {}
wrong_response_count = 0
for k in tqdm(
keys_to_traverse,
desc="Fetching IPFS contents for requests",
position=1,
unit="results",
):
mech_request = mech_requests[k]
if "ipfsContents" not in mech_request:
ipfs_hash = mech_request["ipfsHash"]
url = f"{IPFS_ADDRESS}{ipfs_hash}/metadata.json"
response = request(session, url)
if response is None:
tqdm.write(f"Skipping {mech_request=}. because response was None")
wrong_response_count += 1
continue
try:
contents = response.json()
if contents["tool"] in IRRELEVANT_TOOLS:
continue
mech_request["ipfsContents"] = contents
except requests.exceptions.JSONDecodeError:
tqdm.write(
f"Skipping {mech_request} because of JSONDecodeError when parsing response"
)
wrong_response_count += 1
continue
updated_dict[k] = mech_request
time.sleep(IPFS_POLL_INTERVAL)
return updated_dict, wrong_response_count
def populate_delivers_ipfs_contents(
session: requests.Session, mech_requests: Dict[str, Any], keys_to_traverse: list
) -> dict:
"""Function to complete the delivers content info from ipfs"""
updated_dict = {}
errors = 0
for k in tqdm(
keys_to_traverse,
desc="Fetching IPFS contents for delivers",
position=1,
unit="results",
):
mech_request = mech_requests[k]
if "deliver" not in mech_request or len(mech_request["deliver"]) == 0:
print(f"Skipping mech request {mech_request} because of no delivers info")
continue
deliver = mech_request["deliver"]
if "ipfsContents" not in deliver:
ipfs_hash = deliver["ipfsHash"]
request_id = deliver["requestId"]
url = f"{IPFS_ADDRESS}{ipfs_hash}/{request_id}"
response = request(session, url)
if response is None:
tqdm.write(f"Skipping {mech_request=}.")
continue
try:
contents = response.json()
metadata = contents.get("metadata", None)
if metadata and contents["metadata"]["tool"] in IRRELEVANT_TOOLS:
continue
contents.pop("cost_dict", None)
deliver["ipfsContents"] = contents
except requests.exceptions.JSONDecodeError:
tqdm.write(f"Skipping {mech_request} because of JSONDecodeError")
continue
except Exception:
errors += 1
tqdm.write(
f"Skipping {mech_request} because of error parsing the response"
)
continue
updated_dict[k] = mech_request
time.sleep(IPFS_POLL_INTERVAL)
return updated_dict, errors
def write_mech_events_to_file(
mech_requests: Dict[str, Any],
filename: str,
force_write: bool = False,
) -> None:
global last_write_time # pylint: disable=global-statement
now = time.time()
if len(mech_requests) == 0:
return
filename_path = ROOT_DIR / filename
if force_write or (now - last_write_time) >= MINIMUM_WRITE_FILE_DELAY_SECONDS:
with open(filename_path, "w", encoding="utf-8") as file:
json.dump(mech_requests, file, indent=2)
last_write_time = now
def merge_json_files(old_file: str, new_file: str):
with open(JSON_DATA_DIR / new_file, "r") as f:
new_data = json.load(f)
try:
with open(JSON_DATA_DIR / old_file, "r") as f:
old_data = json.load(f)
old_data.update(new_data)
data_to_save = old_data
except FileNotFoundError:
# if no old file exists, just use new data
data_to_save = new_data
# Save the merged JSON file
print(f"{old_file} updated")
save_json_file(data_to_save, old_file)
def clean_mech_delivers(requests_filename: str, delivers_filename: str) -> None:
"""Function to remove from the delivers json file the request Ids that are not in the mech requests"""
# read mech requests
with open(JSON_DATA_DIR / requests_filename, "r") as file:
mech_requests = json.load(file)
list_reqIds = [mech_requests[k].get("requestId") for k in mech_requests.keys()]
# remove requestIds from delivers that are not in this list
with open(JSON_DATA_DIR / delivers_filename, "r") as file:
mech_delivers = json.load(file)
print(f"original size of the file {len(mech_delivers)}")
mech_delivers = {
k: v
for k, v in tqdm(
mech_delivers.items(),
total=len(mech_delivers),
desc="Filtering delivers dictionary",
)
if k in set(list_reqIds)
}
print(f"final size of the file {len(mech_delivers)}")
save_json_file(mech_delivers, delivers_filename)
def get_request_block_numbers(
mech_requests: Dict[str, Any], target_req_id: int
) -> list:
block_numbers = []
for entry in mech_requests.values():
if entry["requestId"] == target_req_id:
block_numbers.append(entry["blockNumber"])
return block_numbers
def update_block_request_map(block_request_id_map: dict) -> None:
print("Saving block request id map info")
with open(JSON_DATA_DIR / "block_request_id_map.pickle", "wb") as handle:
pickle.dump(block_request_id_map, handle, protocol=pickle.HIGHEST_PROTOCOL)
def fix_duplicate_requestIds(requests_filename: str, delivers_filename: str) -> dict:
print("Fix duplicated request Ids")
with open(JSON_DATA_DIR / delivers_filename, "r") as file:
data_delivers = json.load(file)
with open(JSON_DATA_DIR / requests_filename, "r") as file:
mech_requests = json.load(file)
list_request_Ids = list(data_delivers.keys())
list_duplicated_reqIds = []
for req_Id in list_request_Ids:
if len(data_delivers.get(req_Id)) > 1:
list_duplicated_reqIds.append(req_Id)
print(len(list_duplicated_reqIds))
block_request_id_map = {}
for req_Id in list_duplicated_reqIds:
# get the list of mech request block numbers for that requestId
block_nrs = get_request_block_numbers(mech_requests, req_Id)
# get the list of mech delivers
mech_delivers_list = data_delivers.get(req_Id) # list of dictionaries
if len(block_nrs) > 1:
print("More than one block number was found")
for block_nr in block_nrs:
key = (block_nr, req_Id)
min_difference_request = min(
mech_delivers_list,
key=lambda x: abs(int(x["blockNumber"]) - int(block_nr)),
)
block_request_id_map[key] = min_difference_request
update_block_request_map(block_request_id_map)
return block_request_id_map
def merge_requests_delivers(
requests_filename: str, delivers_filename: str, filename: str
) -> None:
print("Merge request delivers")
"""Function to map requests and delivers"""
with open(JSON_DATA_DIR / delivers_filename, "r") as file:
mech_delivers = json.load(file)
with open(JSON_DATA_DIR / requests_filename, "r") as file:
mech_requests = json.load(file)
# read the block map for duplicated requestIds
with open(JSON_DATA_DIR / "block_request_id_map.pickle", "rb") as handle:
# key = (block_nr, req_Id) value = delivers dictionary
block_request_id_map = pickle.load(handle)
for _, mech_req in tqdm(
mech_requests.items(),
desc=f"Merging delivers data into the mech requests",
):
if "deliver" in mech_req:
continue
block_number_req = mech_req["blockNumber"]
req_Id = mech_req["requestId"]
# check if it is in the duplicated map
key = (block_number_req, req_Id)
if key in block_request_id_map.keys():
deliver_dict = block_request_id_map[key]
elif req_Id in mech_delivers.keys():
deliver_dict = mech_delivers.get(req_Id)[0] # the value is a list
else:
print("No deliver entry found for this request Id")
deliver_dict = collect_missing_delivers(
request_id=req_Id, block_number=int(block_number_req)
)
# extract the info and append it to the original mech request dictionary
mech_req["deliver"] = deliver_dict
save_json_file(mech_requests, filename)
return
def get_ipfs_data(input_filename: str, output_filename: str, logger):
with open(JSON_DATA_DIR / input_filename, "r") as file:
mech_requests = json.load(file)
total_keys_to_traverse = list(mech_requests.keys())
updated_mech_requests = dict()
session = create_session()
logger.info("UPDATING IPFS CONTENTS OF REQUESTS")
# requests
nr_errors = 0
with ThreadPoolExecutor(max_workers=NUM_WORKERS) as executor:
futures = []
for i in range(0, len(mech_requests), GET_CONTENTS_BATCH_SIZE):
futures.append(
executor.submit(
populate_requests_ipfs_contents,
session,
mech_requests,
total_keys_to_traverse[i : i + GET_CONTENTS_BATCH_SIZE],
)
)
for future in tqdm(
as_completed(futures),
total=len(futures),
desc=f"Fetching all ipfs contents from requests ",
):
partial_dict, error_counter = future.result()
nr_errors += error_counter
updated_mech_requests.update(partial_dict)
save_json_file(updated_mech_requests, output_filename)
logger.info(f"NUMBER OF MECH REQUEST IPFS ERRORS={nr_errors}")
# delivers
nr_deliver_errors = 0
logger.info("UPDATING IPFS CONTENTS OF DELIVERS")
total_keys_to_traverse = list(updated_mech_requests.keys())
final_tools_content = {}
with ThreadPoolExecutor(max_workers=NUM_WORKERS) as executor:
futures = []
for i in range(0, len(updated_mech_requests), GET_CONTENTS_BATCH_SIZE):
futures.append(
executor.submit(
populate_delivers_ipfs_contents,
session,
updated_mech_requests,
total_keys_to_traverse[i : i + GET_CONTENTS_BATCH_SIZE],
)
)
for future in tqdm(
as_completed(futures),
total=len(futures),
desc=f"Fetching all ipfs contents from delivers ",
):
partial_dict, error_counter = future.result()
nr_deliver_errors += error_counter
final_tools_content.update(partial_dict)
save_json_file(final_tools_content, output_filename)
logger.info(f"NUMBER OF MECH DELIVERS IPFS ERRORS={nr_deliver_errors}")