From fc7804ee6f8b2bd0b33c1ab53c0ced5cdc20324f Mon Sep 17 00:00:00 2001 From: Matthew Printz Date: Fri, 14 Jul 2023 11:19:54 -0400 Subject: [PATCH] Adding mira model context and handler --- llmkernel/kernel.py | 146 +++- poetry.lock | 1237 +++++++++++++++++--------------- toolsets/dataset_toolset.py | 2 +- toolsets/mira_model_toolset.py | 214 ++++++ 4 files changed, 1005 insertions(+), 594 deletions(-) create mode 100644 toolsets/mira_model_toolset.py diff --git a/llmkernel/kernel.py b/llmkernel/kernel.py index e811361..d4ba405 100644 --- a/llmkernel/kernel.py +++ b/llmkernel/kernel.py @@ -13,6 +13,7 @@ from ipykernel.kernelbase import Kernel from ipykernel.ipkernel import IPythonKernel from toolsets.dataset_toolset import DatasetToolset +from toolsets.mira_model_toolset import MiraModelToolset from archytas.react import ReActAgent logger = logging.getLogger(__name__) @@ -30,49 +31,69 @@ class PythonLLMKernel(IPythonKernel): def setup_instance(self, *args, **kwargs): + self.toolset = None + self.agent = None # Init LLM agent - self.toolset = DatasetToolset() - self.agent = ReActAgent(tools=[self.toolset], allow_ask_user=False, verbose=True, spinner=None, rich_print=False) - self.toolset.agent = self.agent - if getattr(self, 'context', None) is not None: - self.agent.clear_all_context() self.context = None self.msg_types.append("context_setup_request") self.msg_types.append("llm_request") self.msg_types.append("download_dataset_request") self.msg_types.append("save_dataset_request") + self.msg_types.append("save_amr_request") + self.msg_types.append("load_dataset") + self.msg_types.append("load_mira_model") return super().setup_instance(*args, **kwargs) def set_context(self, context, context_info): + self.toolset = None match context: case "dataset": + self.toolset = DatasetToolset() + self.agent = ReActAgent(tools=[self.toolset], allow_ask_user=False, verbose=True, spinner=None, rich_print=False) + self.toolset.agent = self.agent + if getattr(self, 'context', None) is not None: + self.agent.clear_all_context() dataset_id = context_info["id"] print(f"Processing dataset w/id {dataset_id}") - self.toolset.set_dataset(dataset_id) self.toolset.kernel = self.shell + self.toolset.set_dataset(dataset_id) self.context = self.agent.add_context(self.toolset.context()) self.shell.ex("""import pandas as pd; import numpy as np; import scipy;""") self.shell.push({ "df": self.toolset.df }) self.send_df_preview_message() + case "mira_model": + self.toolset = MiraModelToolset() + self.agent = ReActAgent(tools=[self.toolset], allow_ask_user=False, verbose=True, spinner=None, rich_print=False) + self.toolset.agent = self.agent + if getattr(self, 'context', None) is not None: + self.agent.clear_all_context() + model_id = context_info["id"] + print(f"Processing AMR {model_id} as a MIRA model") + self.toolset.kernel = self.shell + self.toolset.set_model(model_id) + self.context = self.agent.add_context(self.toolset.context()) def send_df_preview_message(self): - df = self.shell.ev("df") - if isinstance(df, pd.DataFrame): - split_df = json.loads(df.head(30).to_json(orient="split")) - payload = { - "name": "Temp dataset (not saved)", - "headers": split_df["columns"], - "csv": [split_df["columns"]] + split_df["data"], - } - self.send_response( - stream=self.iopub_socket, - msg_or_type="dataset", - content=payload, - ) + try: + df = self.shell.ev("df") + if isinstance(df, pd.DataFrame): + split_df = json.loads(df.head(30).to_json(orient="split")) + payload = { + "name": "Temp dataset (not saved)", + "headers": split_df["columns"], + "csv": [split_df["columns"]] + split_df["data"], + } + self.send_response( + stream=self.iopub_socket, + msg_or_type="dataset", + content=payload, + ) + except: + pass # def send_response(self, stream, msg_or_type, content=None, ident=None, buffers=None, track=False, header=None, metadata=None, channel="shell"): @@ -87,7 +108,7 @@ async def llm_request(self, queue, message_id, message, **kwargs): if not request: return try: - result = self.agent.react(request) + result = await self.agent.react_async(request) except Exception as err: error_text = f"""LLM Error: {err} @@ -140,6 +161,42 @@ async def context_setup_request(self, queue, message_id, message, **kwargs): channel="iopub", ) + async def load_dataset(self, queue, message_id, message, **kwargs): + content = message.get('content', {}) + dataset_id = content.get('dataset_id', None) + filename = content.get('filename', None) + var_name = content.get('var_name', 'df') + meta_url = f"{os.environ['DATA_SERVICE_URL']}/datasets/{dataset_id}" + if not filename: + dataset_meta = requests.get(meta_url).json() + filename = dataset_meta.get('file_names', [])[0] + data_url_req = requests.get(f'{meta_url}/download-url?filename={filename}') + data_url = data_url_req.json().get('url', None) + self.shell.ex( + """import pandas as pd; import numpy as np; import scipy;\n""" + """import sympy; import itertools; from mira.metamodel import *; from mira.modeling import Model;\n""" + """from mira.modeling.askenet.petrinet import AskeNetPetriNetModel; from mira.modeling.viz import GraphicalModel;\n""" + f"""{var_name} = pd.read_csv({data_url});""" + f"""{var_name};""" + ) + + + async def load_mira_model(self, queue, message_id, message, **kwargs): + content = message.get('content', {}) + model_id = content.get('model_id', None) + var_name = content.get('var_name', 'model') + + model_url = f"{os.environ['DATA_SERVICE_URL']}/models/{model_id}" + + self.shell.ex( + """import requests; import pandas as pd; import numpy as np; import scipy;\n""" + """import json; from mira.sources.askenet.petrinet import template_model_from_askenet_json;\n""" + """import sympy; import itertools; from mira.metamodel import *; from mira.modeling import Model;\n""" + """from mira.modeling.askenet.petrinet import AskeNetPetriNetModel; from mira.modeling.viz import GraphicalModel;\n""" + f"""amr = requests.get({model_url}).json(); {var_name} = template_model_from_askenet_json(amr));""" + f"""${var_name};""" + ) + async def execute_request(self, stream, ident, parent): # Rewrite parent so that this is properly tied to requests in terarium # notebook_item = parent.get('metadata', {}).get('notebook_item', None) @@ -234,6 +291,55 @@ async def save_dataset_request(self, queue, message_id, message, **kwargs): }, channel="iopub", ) + + + async def save_amr_request(self, queue, message_id, message, **kwargs): + self.send_response( + stream=self.iopub_socket, + msg_or_type="status", + content={ + "execution_state": "busy", + }, + channel="iopub", + ) + + content = message.get('content', {}) + parent_model_id = content.get("parent_model_id") + new_name = content.get("name") + var_name = 'model' + + amr = self.shell.ev(f"AskeNetPetriNetModel(Model({var_name})).to_json()") + + parent_url = f"{os.environ['DATA_SERVICE_URL']}/models/{parent_model_id}" + parent_model = requests.get(parent_url).json() + if not parent_model: + raise Exception(f"Unable to locate parent model '{parent_model_id}'") + + new_model = copy.deepcopy(parent_model) + del new_model["id"] + new_model["name"] = new_name + new_model["description"] += f"\nTransformed from model '{parent_model['name']}' ({parent_model['id']}) at {datetime.datetime.utcnow().strftime('%c %Z')}" + + create_req = requests.post(f"{os.environ['DATA_SERVICE_URL']}/models", json=new_model) + new_model_id = create_req.json()["id"] + + self.send_response( + stream=self.iopub_socket, + msg_or_type="save_model_response", + content={ + "model_id": new_model_id, + "parent_model_id": parent_model_id + }, + channel="iopub", + ) + self.send_response( + stream=self.iopub_socket, + msg_or_type="status", + content={ + "execution_state": "idle", + }, + channel="iopub", + ) async def do_execute(self, code, silent, store_history=True, user_expressions=None, allow_stdin=False, *, cell_id=None): result = await super().do_execute(code, silent, store_history, user_expressions, allow_stdin, cell_id=cell_id) diff --git a/poetry.lock b/poetry.lock index 3c46fc4..de6ae62 100644 --- a/poetry.lock +++ b/poetry.lock @@ -51,7 +51,7 @@ docs = ["sphinx (==6.1.3)", "sphinx-mdinclude (==0.5.3)"] [[package]] name = "anyio" -version = "3.7.0" +version = "3.7.1" description = "High level compatibility layer for multiple asynchronous event loop implementations" category = "main" optional = false @@ -63,7 +63,7 @@ idna = ">=2.8" sniffio = ">=1.1" [package.extras] -doc = ["Sphinx (>=6.1.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme", "sphinxcontrib-jquery"] +doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"] test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] trio = ["trio (<0.22)"] @@ -77,7 +77,7 @@ python-versions = "*" [[package]] name = "archytas" -version = "1.0.1" +version = "1.0.3" description = "A library for pairing LLM agents with tools so they perform open ended tasks" category = "main" optional = false @@ -238,7 +238,7 @@ pycparser = "*" [[package]] name = "charset-normalizer" -version = "3.1.0" +version = "3.2.0" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." category = "main" optional = false @@ -270,7 +270,7 @@ typing = ["mypy (>=0.990)"] [[package]] name = "contourpy" -version = "1.0.7" +version = "1.1.0" description = "Python library for calculating contours of 2D quadrilateral grids" category = "main" optional = false @@ -280,11 +280,11 @@ python-versions = ">=3.8" numpy = ">=1.16" [package.extras] -bokeh = ["bokeh", "chromedriver", "selenium"] +bokeh = ["bokeh", "selenium"] docs = ["furo", "sphinx-copybutton"] -mypy = ["contourpy[bokeh]", "docutils-stubs", "mypy (==0.991)", "types-Pillow"] -test = ["Pillow", "matplotlib", "pytest"] -test-no-images = ["pytest"] +mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.2.0)", "types-Pillow"] +test = ["Pillow", "contourpy[test-no-images]", "matplotlib"] +test-no-images = ["pytest", "pytest-cov", "wurlitzer"] [[package]] name = "cycler" @@ -328,7 +328,7 @@ python-versions = ">=3.6,<4.0" [[package]] name = "exceptiongroup" -version = "1.1.1" +version = "1.1.2" description = "Backport of PEP 654 (exception groups)" category = "main" optional = false @@ -361,7 +361,7 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc [[package]] name = "fonttools" -version = "4.39.4" +version = "4.41.0" description = "Tools to manipulate font files" category = "main" optional = false @@ -399,11 +399,11 @@ python-versions = ">=3.6" [[package]] name = "frozenlist" -version = "1.3.3" +version = "1.4.0" description = "A list-like structure which implements collections.abc.MutableSequence" category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" [[package]] name = "idna" @@ -415,7 +415,7 @@ python-versions = ">=3.5" [[package]] name = "ipykernel" -version = "6.23.1" +version = "6.24.0" description = "IPython Kernel for Jupyter" category = "main" optional = false @@ -445,7 +445,7 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio" [[package]] name = "ipython" -version = "8.13.2" +version = "8.14.0" description = "IPython: Productive Interactive Computing" category = "main" optional = false @@ -540,29 +540,31 @@ dev = ["hypothesis"] [[package]] name = "jsonpointer" -version = "2.3" +version = "2.4" description = "Identify specific nodes in a JSON document (RFC 6901)" category = "main" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*" [[package]] name = "jsonschema" -version = "4.17.3" +version = "4.18.3" description = "An implementation of JSON Schema validation for Python" category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" [package.dependencies] -attrs = ">=17.4.0" +attrs = ">=22.2.0" fqdn = {version = "*", optional = true, markers = "extra == \"format-nongpl\""} idna = {version = "*", optional = true, markers = "extra == \"format-nongpl\""} isoduration = {version = "*", optional = true, markers = "extra == \"format-nongpl\""} jsonpointer = {version = ">1.13", optional = true, markers = "extra == \"format-nongpl\""} -pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2" +jsonschema-specifications = ">=2023.03.6" +referencing = ">=0.28.4" rfc3339-validator = {version = "*", optional = true, markers = "extra == \"format-nongpl\""} rfc3986-validator = {version = ">0.1.0", optional = true, markers = "extra == \"format-nongpl\""} +rpds-py = ">=0.7.1" uri-template = {version = "*", optional = true, markers = "extra == \"format-nongpl\""} webcolors = {version = ">=1.11", optional = true, markers = "extra == \"format-nongpl\""} @@ -570,9 +572,20 @@ webcolors = {version = ">=1.11", optional = true, markers = "extra == \"format-n format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"] format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"] +[[package]] +name = "jsonschema-specifications" +version = "2023.6.1" +description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry" +category = "main" +optional = false +python-versions = ">=3.8" + +[package.dependencies] +referencing = ">=0.28.0" + [[package]] name = "jupyter-client" -version = "8.2.0" +version = "8.3.0" description = "Jupyter protocol implementation and client libraries" category = "main" optional = false @@ -591,7 +604,7 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt [[package]] name = "jupyter-core" -version = "5.3.0" +version = "5.3.1" description = "Jupyter core package. A base package on which Jupyter projects rely." category = "main" optional = false @@ -629,7 +642,7 @@ test = ["click", "coverage", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>= [[package]] name = "jupyter-server" -version = "2.6.0" +version = "2.7.0" description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." category = "main" optional = false @@ -658,7 +671,7 @@ websocket-client = "*" [package.extras] docs = ["ipykernel", "jinja2", "jupyter-client", "jupyter-server", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi (>=0.8.0)", "sphinxcontrib-spelling", "sphinxemoji", "tornado", "typing-extensions"] -test = ["ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.4)", "pytest-timeout", "requests"] +test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.4)", "pytest-timeout", "requests"] [[package]] name = "jupyter-server-fileid" @@ -725,7 +738,7 @@ test = ["pre-commit", "pytest", "pytest-asyncio", "websockets (>=10.0)", "ypy-we [[package]] name = "jupyterlab" -version = "3.6.4" +version = "3.6.5" description = "JupyterLab computational environment" category = "main" optional = false @@ -758,7 +771,7 @@ python-versions = ">=3.7" [[package]] name = "jupyterlab-server" -version = "2.22.1" +version = "2.23.0" description = "A set of server components for JupyterLab and JupyterLab like applications." category = "main" optional = false @@ -774,7 +787,7 @@ packaging = ">=21.3" requests = ">=2.28" [package.extras] -docs = ["autodoc-traits", "docutils (<0.20)", "jinja2 (<3.2.0)", "mistune (<3)", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinxcontrib-openapi"] +docs = ["autodoc-traits", "jinja2 (<3.2.0)", "mistune (<4)", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinxcontrib-openapi (>0.8)"] openapi = ["openapi-core (>=0.16.1,<0.17.0)", "ruamel-yaml"] test = ["hatch", "ipykernel", "jupyterlab-server[openapi]", "openapi-spec-validator (>=0.5.1,<0.6.0)", "pytest (>=7.0)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"] @@ -788,11 +801,11 @@ python-versions = ">=3.7" [[package]] name = "markdown-it-py" -version = "2.2.0" +version = "3.0.0" description = "Python port of markdown-it. Markdown parsing, done right!" category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" [package.dependencies] mdurl = ">=0.1,<1.0" @@ -804,12 +817,12 @@ compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0 linkify = ["linkify-it-py (>=1,<3)"] plugins = ["mdit-py-plugins"] profiling = ["gprof2dot"] -rtd = ["attrs", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"] +rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"] testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"] [[package]] name = "markupsafe" -version = "2.1.2" +version = "2.1.3" description = "Safely add untrusted strings to HTML/XML markup." category = "main" optional = false @@ -817,7 +830,7 @@ python-versions = ">=3.7" [[package]] name = "matplotlib" -version = "3.7.1" +version = "3.7.2" description = "Python plotting package" category = "main" optional = false @@ -831,7 +844,7 @@ kiwisolver = ">=1.0.1" numpy = ">=1.20" packaging = ">=20.0" pillow = ">=6.2.0" -pyparsing = ">=2.3.1" +pyparsing = ">=2.3.1,<3.1" python-dateutil = ">=2.7" setuptools_scm = ">=7" @@ -856,11 +869,11 @@ python-versions = ">=3.7" [[package]] name = "mistune" -version = "2.0.5" -description = "A sane Markdown parser with useful plugins and renderers" +version = "3.0.1" +description = "A sane and fast Markdown parser with useful plugins and renderers" category = "main" optional = false -python-versions = "*" +python-versions = ">=3.7" [[package]] name = "multidict" @@ -923,7 +936,7 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>= [[package]] name = "nbconvert" -version = "7.4.0" +version = "7.6.0" description = "Converting Jupyter Notebooks" category = "main" optional = false @@ -931,20 +944,20 @@ python-versions = ">=3.7" [package.dependencies] beautifulsoup4 = "*" -bleach = "*" +bleach = "!=5.0.0" defusedxml = "*" jinja2 = ">=3.0" jupyter-core = ">=4.7" jupyterlab-pygments = "*" markupsafe = ">=2.0" -mistune = ">=2.0.3,<3" +mistune = ">=2.0.3,<4" nbclient = ">=0.5.0" -nbformat = ">=5.1" +nbformat = ">=5.7" packaging = "*" pandocfilters = ">=1.4.1" pygments = ">=2.4.1" tinycss2 = "*" -traitlets = ">=5.0" +traitlets = ">=5.1" [package.extras] all = ["nbconvert[docs,qtpdf,serve,test,webpdf]"] @@ -957,7 +970,7 @@ webpdf = ["pyppeteer (>=1,<1.1)"] [[package]] name = "nbformat" -version = "5.9.0" +version = "5.9.1" description = "The Jupyter Notebook format" category = "main" optional = false @@ -1028,15 +1041,15 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync" [[package]] name = "numpy" -version = "1.24.3" +version = "1.25.1" description = "Fundamental package for array computing in Python" category = "main" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" [[package]] name = "openai" -version = "0.27.7" +version = "0.27.8" description = "Python client library for the OpenAI API" category = "main" optional = false @@ -1071,7 +1084,7 @@ python-versions = ">=3.7" [[package]] name = "pandas" -version = "2.0.2" +version = "2.0.3" description = "Powerful data structures for data analysis, time series, and statistics" category = "main" optional = false @@ -1087,7 +1100,7 @@ pytz = ">=2020.1" tzdata = ">=2022.1" [package.extras] -all = ["PyQt5 (>=5.15.1)", "SQLAlchemy (>=1.4.16)", "beautifulsoup4 (>=4.9.3)", "bottleneck (>=1.3.2)", "brotlipy (>=0.7.0)", "fastparquet (>=0.6.3)", "fsspec (>=2021.07.0)", "gcsfs (>=2021.07.0)", "html5lib (>=1.1)", "hypothesis (>=6.34.2)", "jinja2 (>=3.0.0)", "lxml (>=4.6.3)", "matplotlib (>=3.6.1)", "numba (>=0.53.1)", "numexpr (>=2.7.3)", "odfpy (>=1.4.1)", "openpyxl (>=3.0.7)", "pandas-gbq (>=0.15.0)", "psycopg2 (>=2.8.6)", "pyarrow (>=7.0.0)", "pymysql (>=1.0.2)", "pyreadstat (>=1.1.2)", "pytest (>=7.0.0)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)", "python-snappy (>=0.6.0)", "pyxlsb (>=1.0.8)", "qtpy (>=2.2.0)", "s3fs (>=2021.08.0)", "scipy (>=1.7.1)", "tables (>=3.6.1)", "tabulate (>=0.8.9)", "xarray (>=0.21.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=1.4.3)", "zstandard (>=0.15.2)"] +all = ["PyQt5 (>=5.15.1)", "SQLAlchemy (>=1.4.16)", "beautifulsoup4 (>=4.9.3)", "bottleneck (>=1.3.2)", "brotlipy (>=0.7.0)", "fastparquet (>=0.6.3)", "fsspec (>=2021.07.0)", "gcsfs (>=2021.07.0)", "html5lib (>=1.1)", "hypothesis (>=6.34.2)", "jinja2 (>=3.0.0)", "lxml (>=4.6.3)", "matplotlib (>=3.6.1)", "numba (>=0.53.1)", "numexpr (>=2.7.3)", "odfpy (>=1.4.1)", "openpyxl (>=3.0.7)", "pandas-gbq (>=0.15.0)", "psycopg2 (>=2.8.6)", "pyarrow (>=7.0.0)", "pymysql (>=1.0.2)", "pyreadstat (>=1.1.2)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)", "python-snappy (>=0.6.0)", "pyxlsb (>=1.0.8)", "qtpy (>=2.2.0)", "s3fs (>=2021.08.0)", "scipy (>=1.7.1)", "tables (>=3.6.1)", "tabulate (>=0.8.9)", "xarray (>=0.21.0)", "xlrd (>=2.0.1)", 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filename=None, var_name="df"): if filename is None: filename = self.dataset.get('file_names', [])[0] meta_url = f"{os.environ['DATA_SERVICE_URL']}/datasets/{self.dataset_id}" diff --git a/toolsets/mira_model_toolset.py b/toolsets/mira_model_toolset.py new file mode 100644 index 0000000..ff1cc91 --- /dev/null +++ b/toolsets/mira_model_toolset.py @@ -0,0 +1,214 @@ +import json +import logging +import os +import re +import requests +from typing import Optional, Any + +import pandas as pd + +from archytas.tool_utils import tool, toolset, AgentRef, LoopControllerRef + +logging.disable(logging.WARNING) # Disable warnings +logger = logging.Logger(__name__) + + +@toolset() +class MiraModelToolset: + """ """ + + model_id: Optional[str] + model_json: Optional[str] + model_dict: Optional[dict[str, Any]] + var_name: Optional[str] = 'model' + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.reset() + + def set_model(self, model_id, agent=None): + self.model_id = model_id + meta_url = f"{os.environ['DATA_SERVICE_URL']}/models/{self.model_id}" + self.amr = requests.get(meta_url).json() + if self.amr: + self.load_mira() + else: + raise Exception(f"Model '{model_id}' not found.") + + def load_mira(self): + command = ( + """import requests; import pandas as pd; import numpy as np; import scipy;\n""" + """import json; import mira; from mira.modeling.askenet.petrinet import AskeNetPetriNetModel; from mira.sources.askenet.petrinet import template_model_from_askenet_json;\n""" + """import sympy; import itertools; from mira.metamodel import *; from mira.modeling import Model;\n""" + """from mira.modeling.askenet.petrinet import AskeNetPetriNetModel; from mira.modeling.viz import GraphicalModel;\n""" + f"""{self.var_name} = template_model_from_askenet_json({self.amr});\n""" + ) + self.kernel.ex(command) + + def reset(self): + self.model_id = None + self.df = None + + def context(self): + return f"""You are an scientific modeler whose goal is to use the MIRA modeling library to manipulate and stratify Petrinet models in Python. + +You are working on a Petrinet model named: {self.amr.get('name')} + +The description of the model is: +{self.amr.get('description')} + +The model has the following structure: +--- START --- +{self.model_structure()} +--- END --- + +Please answer any user queries to the best of your ability, but do not guess if you are not sure of an answer. +If you are asked to manipulate, stratify, or visualize the model, use the generate_python_code tool. +""" + + @tool() + def model_structure(self) -> str: + """ + Inspect the model and return information and metadata about it. + + This should be used to answer questions about the model, including information about the states, populations, transistions, etc. + + + Returns: + str: a textual representation of the model + """ + # Update the local dataframe to match what's in the shell. + # This will be factored out when we switch around to allow using multiple runtimes. + if self.kernel: + amr = self.kernel.ev(f"AskeNetPetriNetModel(Model({self.var_name})).to_json()") + return json.dumps(amr, indent=2) + return "UNDEFINED" + + + @tool() + def generate_python_code( + self, query: str, agent: AgentRef, loop: LoopControllerRef + ) -> str: + """ + Generated Python code to be run in an interactive Jupyter notebook for the purpose of exploring, modifying and visualizing a Pandas Dataframe. + + Input is a full grammatically correct question about or request for an action to be performed on the loaded model. + + Assume that the model is already loaded and has the variable named `model`. + Information about the dataframe can be loaded with the `model_structure` tool. + + Args: + query (str): A fully grammatically correct queistion about the current model. + + Returns: + str: A LLM prompt that should be passed evaluated. + """ + # set up the agent + # str: Valid and correct python code that fulfills the user's request. + prompt = f""" +You are a programmer writing code to help with scientific data analysis and manipulation in Python. + +Please write code that satisfies the user's request below. + +You have access to a variable name `model` that is a Petrinet model with the following structure: +{self.model_structure()} + + +If you are asked to modify or update the model, modify the model in place, keeping the updated variable to still be named `model`. +You have access to the MIRA libraries. + +If you are asked to stratify the model, use the available function named `stratify` that is defined by the following python code: +```````````````````` +def stratify( + template_model: TemplateModel, + *, + key: str, + strata: Collection[str], + structure: Optional[Iterable[Tuple[str, str]]] = None, + directed: bool = False, + conversion_cls: Type[Template] = NaturalConversion, + cartesian_control: bool = False, + modify_names: bool = True, + params_to_stratify: Optional[Collection[str]] = None, + params_to_preserve: Optional[Collection[str]] = None, + concepts_to_stratify: Optional[Collection[str]] = None, + concepts_to_preserve: Optional[Collection[str]] = None, +) -> TemplateModel: + \"\"\"Multiplies a model into several strata. + + E.g., can turn the SIR model into a two-city SIR model by splitting each concept into + two derived concepts, each with the context for one of the two cities + + Parameters + ---------- + template_model : + A template model + key : + The (singular) name of the stratification, e.g., ``"city"`` + strata : + A list of the values for stratification, e.g., ``["boston", "nyc"]`` + structure : + An iterable of pairs corresponding to a directed network structure + where each of the pairs has two strata. If none given, will assume a complete + network structure. If no structure is necessary, pass an empty list. + directed : + Should the reverse direction conversions be added based on the given structure? + conversion_cls : + The template class to be used for conversions between strata + defined by the network structure. Defaults to :class:`NaturalConversion` + cartesian_control : + If true, splits all control relationships based on the stratification. + + This should be true for an SIR epidemiology model, the susceptibility to + infected transition is controlled by infected. If the model is stratified by + vaccinated and unvaccinated, then the transition from vaccinated + susceptible population to vaccinated infected populations should be + controlled by both infected vaccinated and infected unvaccinated + populations. + + This should be false for stratification of an SIR epidemiology model based + on cities, since the infected population in one city won't (directly, + through the perspective of the model) affect the infection of susceptible + population in another city. + modify_names : + If true, will modify the names of the concepts to include the strata + (e.g., ``"S"`` becomes ``"S_boston"``). If false, will keep the original + names. + params_to_stratify : + A list of parameters to stratify. If none given, will stratify all + parameters. + params_to_preserve: + A list of parameters to preserve. If none given, will stratify all + parameters. + concepts_to_stratify : + A list of concepts to stratify. If none given, will stratify all + concepts. + concepts_to_preserve: + A list of concepts to preserve. If none given, will stratify all + concepts. + + Returns + ------- + : + A stratified template model + \"\"\" +```````````````````` + +You also have access to the libraries pandas, numpy, scipy, matplotlib and the full mira python library. + +Please generate the code as if you were programming inside a Jupyter Notebook and the code is to be executed inside a cell. +You MUST wrap the code with a line containing three backticks (```) before and after the generated code. +No addtional text is needed in the response, just the code block. +""" + + llm_response = agent.oneshot(prompt=prompt, query=query) + loop.set_state(loop.STOP_SUCCESS) + preamble, code, coda = re.split("```\w*", llm_response) + result = json.dumps( + { + "action": "code_cell", + "language": "python", + "content": code.strip(), + } + ) + return result