- ✅ Full integration with Mimir's memory bank
- ✅ Graph functions enable multi-hop reasoning
GitHub Copilot Custom Agent Mode
I modified that beast mode to be more robust, and I love it. Refactored an entire older repo I made from years ago just for fun and was able to do perfectly
I call it "Extensive Mode"
"Extensive Mode.chatmode.md"
The tools should be customized per environment and what you have available,
| description | tools | |||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4.1 Beast Mode |
|
Beast Mode v3 is out now: 👉 https://gist.github.com/burkeholland/88af0249c4b6aff3820bf37898c8bacf
You are an agent - please keep going until the user’s query is completely resolved, before ending your turn and yielding back to the user.
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Requirement
- USB flash drive - this is where the container filesystem will be persisted
Set-up docker bridge network
/interface bridge add name=docker
Set-up veth to be used by container
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| (?i)((access_key|access_token|admin_pass|admin_user|algolia_admin_key|algolia_api_key|alias_pass|alicloud_access_key|amazon_secret_access_key|amazonaws|ansible_vault_password|aos_key|api_key|api_key_secret|api_key_sid|api_secret|api.googlemaps AIza|apidocs|apikey|apiSecret|app_debug|app_id|app_key|app_log_level|app_secret|appkey|appkeysecret|application_key|appsecret|appspot|auth_token|authorizationToken|authsecret|aws_access|aws_access_key_id|aws_bucket|aws_key|aws_secret|aws_secret_key|aws_token|AWSSecretKey|b2_app_key|bashrc password|bintray_apikey|bintray_gpg_password|bintray_key|bintraykey|bluemix_api_key|bluemix_pass|browserstack_access_key|bucket_password|bucketeer_aws_access_key_id|bucketeer_aws_secret_access_key|built_branch_deploy_key|bx_password|cache_driver|cache_s3_secret_key|cattle_access_key|cattle_secret_key|certificate_password|ci_deploy_password|client_secret|client_zpk_secret_key|clojars_password|cloud_api_key|cloud_watch_aws_access_key|cloudant_password|cloudflare_api_key|cloudflare_auth_k |
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| # high-low spread estimator (hlse) | |
| def hlse(ohlc_df, frequency='daily'): | |
| """ | |
| Computes the high-low spread estimator, an estimate of bid-offer spreads, a measure of liquidity risk. | |
| See Corwin & Schultz (2011) for details: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1106193 | |
| Parameters | |
| ---------- | |
| ohlc_df: DataFrame | |
| DataFrame with DatetimeIndex and Open, High, Low and Close (OHLC) prices from which to compute the high-low spread estimates. |
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| import pandas as pd | |
| import numpy as np | |
| import datetime as dt | |
| import math | |
| import warnings | |
| warnings.filterwarnings("ignore") | |
| prices = pd.read_csv("adjclose.csv", index_col="Date", parse_dates=True) | |
| volumechanges = pd.read_csv("volume.csv", index_col="Date", parse_dates=True).pct_change()*100 |
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