diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..a2f3ebf --- /dev/null +++ b/.env.example @@ -0,0 +1,44 @@ +# Copy this file to ``.env`` and fill in values for your environment. +# ``python-dotenv`` is loaded by ``gee_mcp.server.auth`` on import, so any +# variables set here will be picked up automatically when the server +# starts. + +# ---------------------------------------------------------------------- +# Gemini (pick ONE of the two paths below) +# ---------------------------------------------------------------------- + +# Path A — Gemini Developer API key +# GEMINI_API_KEY= +# GOOGLE_API_KEY= + +# Path B — Vertex AI project (requires ``gcloud auth +# application-default login`` to have been run) +# VERTEXAI_PROJECT=your-vertexai-project +# VERTEXAI_LOCATION=global + +# ---------------------------------------------------------------------- +# Google Earth Engine +# ---------------------------------------------------------------------- +# +# Auth is delegated to ``ee.Initialize`` which walks the standard +# Google Cloud credential chain (GOOGLE_APPLICATION_CREDENTIALS, +# gcloud ADC, the ``earthengine authenticate`` cache, GCE metadata). +# You typically just need GEE_PROJECT after running +# ``earthengine authenticate`` or ``gcloud auth application-default login``. + +# Required: GEE project id used for ``ee.Initialize(project=...)``. +GEE_PROJECT=your-gee-project + +# Optional: path to a service-account JSON key file. Set this when +# running headlessly (CI, Cloud Run, etc.) without interactive +# authentication. +# GOOGLE_APPLICATION_CREDENTIALS=/absolute/path/to/service-account.json + +# ---------------------------------------------------------------------- +# Test / CI escape hatch +# ---------------------------------------------------------------------- + +# Set to ``1`` to skip GEE auth entirely on import. Used by the test +# suite to avoid hitting the auth chain in CI. Do not set for normal +# use. +# GEE_SKIP_AUTH=1 diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml new file mode 100644 index 0000000..491d575 --- /dev/null +++ b/.github/workflows/main.yml @@ -0,0 +1,34 @@ +on: push +jobs: + test: + strategy: + matrix: + python-version: ['3.11', '3.12', '3.13', '3.14'] + defaults: + run: + shell: bash + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python-version }} + - name: Install Poetry + uses: snok/install-poetry@v1 + with: + virtualenvs-create: true + virtualenvs-in-project: true + installer-parallel: true + - name: Cache Poetry dependencies + uses: actions/cache@v4 + with: + path: .venv + key: venv-${{ runner.os }}-${{ matrix.python-version }}-${{ hashFiles('poetry.lock') }} + restore-keys: | + venv-${{ runner.os }}-${{ matrix.python-version }}- + - name: Install dependencies + run: | + poetry install --no-interaction + - name: Running pre-commit + uses: pre-commit/action@v3.0.1 diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..0fa91a8 --- /dev/null +++ b/.gitignore @@ -0,0 +1,99 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[codz] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +download/ +eggs/ +.eggs/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py.cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Logs +*.log + +# Translations +*.mo +*.pot + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# Environments +.env +.envrc +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Tooling caches +.mypy_cache/ +.dmypy.json +dmypy.json +.pyre/ +.pytype/ +.ruff_cache/ + +# Editors +.vscode/ +.idea/ + +# Project-specific +.config/ +*.tif +download/ +CLAUDE.md diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..dd31bd4 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,69 @@ +repos: + - repo: local + hooks: + - id: detect-secrets + name: Detect secrets + language: system + entry: poetry run detect-secrets-hook + args: ['--baseline', '.secrets.baseline'] + exclude: '\.ipynb$' + - id: autoflake + name: autoflake + language: system + "types": [python] + require_serial: true + entry: poetry run autoflake + args: + - "--in-place" + - "--remove-unused-variables" + - "--recursive" + - id: black + name: black + entry: poetry run black . + language: system + types: [python] + - id: isort + name: isort + entry: poetry run isort . + language: system + exclude: | + (?x)^( + .+\.js$| + .+\.jsx$| + .+\.css$| + .+\.html$| + .+\.json$| + .+\.md$ + )$ + - id: mypy + name: mypy + entry: poetry run mypy src tests + pass_filenames: false + language: system + args: + - "--ignore-missing-imports" + - "--warn-unused-ignores" + - id: pylint + name: pylint + entry: poetry run pylint src tests + pass_filenames: false + language: system + args: + - "--enable-useless-suppression" + - id: pytest-with-coverage + name: Run pytest with coverage + entry: poetry run coverage run -m pytest --testdox tests + language: system + pass_filenames: false + always_run: true + - id: coverage-report + name: Coverage report + entry: poetry run coverage report + language: system + pass_filenames: false + verbose: true + args: + - "--fail-under=20" + - "--skip-empty" + - "--skip-covered" + - "--show-missing" diff --git a/.pylintrc b/.pylintrc new file mode 100644 index 0000000..9783ff9 --- /dev/null +++ b/.pylintrc @@ -0,0 +1,672 @@ +[MAIN] +init-hook='import sys; sys.path.append("src")' + +# Analyse import fallback blocks. This can be used to support both Python 2 and +# 3 compatible code, which means that the block might have code that exists +# only in one or another interpreter, leading to false positives when analysed. +analyse-fallback-blocks=no + +# Clear in-memory caches upon conclusion of linting. Useful if running pylint +# in a server-like mode. +clear-cache-post-run=no + +# Load and enable all available extensions. Use --list-extensions to see a list +# all available extensions. +#enable-all-extensions= + +# In error mode, messages with a category besides ERROR or FATAL are +# suppressed, and no reports are done by default. Error mode is compatible with +# disabling specific errors. +#errors-only= + +# Always return a 0 (non-error) status code, even if lint errors are found. +# This is primarily useful in continuous integration scripts. +#exit-zero= + +# A comma-separated list of package or module names from where C extensions may +# be loaded. Extensions are loading into the active Python interpreter and may +# run arbitrary code. +extension-pkg-allow-list= + +# A comma-separated list of package or module names from where C extensions may +# be loaded. Extensions are loading into the active Python interpreter and may +# run arbitrary code. (This is an alternative name to extension-pkg-allow-list +# for backward compatibility.) +extension-pkg-whitelist= + +# Return non-zero exit code if any of these messages/categories are detected, +# even if score is above --fail-under value. Syntax same as enable. Messages +# specified are enabled, while categories only check already-enabled messages. +fail-on= + +# Specify a score threshold under which the program will exit with error. +fail-under=7 + +# Interpret the stdin as a python script, whose filename needs to be passed as +# the module_or_package argument. +#from-stdin= + +# Files or directories to be skipped. They should be base names, not paths. +ignore=CVS + +# Add files or directories matching the regular expressions patterns to the +# ignore-list. The regex matches against paths and can be in Posix or Windows +# format. Because '\\' represents the directory delimiter on Windows systems, +# it can't be used as an escape character. +ignore-paths= + +# Files or directories matching the regular expression patterns are skipped. +# The regex matches against base names, not paths. The default value ignores +# Emacs file locks +ignore-patterns=^\.# + +# List of module names for which member attributes should not be checked +# (useful for modules/projects where namespaces are manipulated during runtime +# and thus existing member attributes cannot be deduced by static analysis). It +# supports qualified module names, as well as Unix pattern matching. +ignored-modules= + +# Python code to execute, usually for sys.path manipulation such as +# pygtk.require(). +#init-hook= + +# Use multiple processes to speed up Pylint. Specifying 0 will auto-detect the +# number of processors available to use, and will cap the count on Windows to +# avoid hangs. +jobs=1 + +# Control the amount of potential inferred values when inferring a single +# object. This can help the performance when dealing with large functions or +# complex, nested conditions. +limit-inference-results=100 + +# List of plugins (as comma separated values of python module names) to load, +# usually to register additional checkers. +load-plugins= + pylint_per_file_ignores + +# Pickle collected data for later comparisons. +persistent=yes + +# Minimum Python version to use for version dependent checks. Will default to +# the version used to run pylint. +# py-version=3.12 + +# Discover python modules and packages in the file system subtree. +recursive=no + +# Add paths to the list of the source roots. Supports globbing patterns. The +# source root is an absolute path or a path relative to the current working +# directory used to determine a package namespace for modules located under the +# source root. +source-roots= + +# When enabled, pylint would attempt to guess common misconfiguration and emit +# user-friendly hints instead of false-positive error messages. +suggestion-mode=yes + +# Allow loading of arbitrary C extensions. Extensions are imported into the +# active Python interpreter and may run arbitrary code. +unsafe-load-any-extension=no + +# In verbose mode, extra non-checker-related info will be displayed. +#verbose= + + +[BASIC] + +# Naming style matching correct argument names. +argument-naming-style=snake_case + +# Regular expression matching correct argument names. Overrides argument- +# naming-style. If left empty, argument names will be checked with the set +# naming style. +#argument-rgx= + +# Naming style matching correct attribute names. +attr-naming-style=snake_case + +# Regular expression matching correct attribute names. Overrides attr-naming- +# style. If left empty, attribute names will be checked with the set naming +# style. +#attr-rgx= + +# Bad variable names which should always be refused, separated by a comma. +bad-names=foo, + bar, + baz, + toto, + tutu, + tata + +# Bad variable names regexes, separated by a comma. If names match any regex, +# they will always be refused +bad-names-rgxs= + +# Naming style matching correct class attribute names. +class-attribute-naming-style=any + +# Regular expression matching correct class attribute names. Overrides class- +# attribute-naming-style. If left empty, class attribute names will be checked +# with the set naming style. +#class-attribute-rgx= + +# Naming style matching correct class constant names. +class-const-naming-style=UPPER_CASE + +# Regular expression matching correct class constant names. Overrides class- +# const-naming-style. If left empty, class constant names will be checked with +# the set naming style. +#class-const-rgx= + +# Naming style matching correct class names. +class-naming-style=PascalCase + +# Regular expression matching correct class names. Overrides class-naming- +# style. If left empty, class names will be checked with the set naming style. +#class-rgx= + +# Naming style matching correct constant names. +const-naming-style=UPPER_CASE + +# Regular expression matching correct constant names. Overrides const-naming- +# style. If left empty, constant names will be checked with the set naming +# style. +#const-rgx= + +# Minimum line length for functions/classes that require docstrings, shorter +# ones are exempt. +docstring-min-length=-1 + +# Naming style matching correct function names. +function-naming-style=snake_case + +# Regular expression matching correct function names. Overrides function- +# naming-style. If left empty, function names will be checked with the set +# naming style. +#function-rgx= + +# Good variable names which should always be accepted, separated by a comma. +good-names=i, + j, + k, + ex, + Run, + _ + +# Good variable names regexes, separated by a comma. If names match any regex, +# they will always be accepted +good-names-rgxs= + +# Include a hint for the correct naming format with invalid-name. +include-naming-hint=no + +# Naming style matching correct inline iteration names. +inlinevar-naming-style=any + +# Regular expression matching correct inline iteration names. Overrides +# inlinevar-naming-style. If left empty, inline iteration names will be checked +# with the set naming style. +#inlinevar-rgx= + +# Naming style matching correct method names. +method-naming-style=snake_case + +# Regular expression matching correct method names. Overrides method-naming- +# style. If left empty, method names will be checked with the set naming style. +#method-rgx= + +# Naming style matching correct module names. +module-naming-style=snake_case + +# Regular expression matching correct module names. Overrides module-naming- +# style. If left empty, module names will be checked with the set naming style. +#module-rgx= + +# Colon-delimited sets of names that determine each other's naming style when +# the name regexes allow several styles. +name-group= + +# Regular expression which should only match function or class names that do +# not require a docstring. +no-docstring-rgx=^_ + +# List of decorators that produce properties, such as abc.abstractproperty. Add +# to this list to register other decorators that produce valid properties. +# These decorators are taken in consideration only for invalid-name. +property-classes=abc.abstractproperty + +# Regular expression matching correct type alias names. If left empty, type +# alias names will be checked with the set naming style. +#typealias-rgx= + +# Regular expression matching correct type variable names. If left empty, type +# variable names will be checked with the set naming style. +#typevar-rgx= + +# Naming style matching correct variable names. +variable-naming-style=snake_case + +# Regular expression matching correct variable names. Overrides variable- +# naming-style. If left empty, variable names will be checked with the set +# naming style. +#variable-rgx= + + +[CLASSES] + +# Warn about protected attribute access inside special methods +check-protected-access-in-special-methods=no + +# List of method names used to declare (i.e. assign) instance attributes. +defining-attr-methods=__init__, + __new__, + setUp, + asyncSetUp, + __post_init__ + +# List of member names, which should be excluded from the protected access +# warning. +exclude-protected=_asdict,_fields,_replace,_source,_make,os._exit + +# List of valid names for the first argument in a class method. +valid-classmethod-first-arg=cls + +# List of valid names for the first argument in a metaclass class method. +valid-metaclass-classmethod-first-arg=mcs + + +[DESIGN] + +# List of regular expressions of class ancestor names to ignore when counting +# public methods (see R0903) +exclude-too-few-public-methods= + +# List of qualified class names to ignore when counting class parents (see +# R0901) +ignored-parents= + +# Maximum number of arguments for function / method. +max-args=50 + +# Maximum number of attributes for a class (see R0902). +max-attributes=70 + +# Maximum number of boolean expressions in an if statement (see R0916). +max-bool-expr=5 + +# Maximum number of branch for function / method body. +max-branches=120 + +# Maximum number of locals for function / method body. +max-locals=150 + +# Maximum number of parents for a class (see R0901). +max-parents=7 + +# Maximum number of public methods for a class (see R0904). +max-public-methods=20 + +# Maximum number of return / yield for function / method body. +max-returns=6 + +# Maximum number of statements in function / method body. +max-statements=50 + +# Minimum number of public methods for a class (see R0903). +min-public-methods=2 + + +[EXCEPTIONS] + +# Exceptions that will emit a warning when caught. +overgeneral-exceptions=builtins.BaseException,builtins.Exception + + +[FORMAT] + +# Expected format of line ending, e.g. empty (any line ending), LF or CRLF. +expected-line-ending-format= + +# Regexp for a line that is allowed to be longer than the limit. +ignore-long-lines=^\s*(# )??$ + +# Number of spaces of indent required inside a hanging or continued line. +indent-after-paren=4 + +# String used as indentation unit. This is usually " " (4 spaces) or "\t" (1 +# tab). +indent-string=' ' + +# Maximum number of characters on a single line. +max-line-length=100 + +# Maximum number of lines in a module. +max-module-lines=1000 + +# Allow the body of a class to be on the same line as the declaration if body +# contains single statement. +single-line-class-stmt=no + +# Allow the body of an if to be on the same line as the test if there is no +# else. +single-line-if-stmt=no + + +[IMPORTS] + +# List of modules that can be imported at any level, not just the top level +# one. +allow-any-import-level= + +# Allow explicit reexports by alias from a package __init__. +allow-reexport-from-package=no + +# Allow wildcard imports from modules that define __all__. +allow-wildcard-with-all=no + +# Deprecated modules which should not be used, separated by a comma. +deprecated-modules= + +# Output a graph (.gv or any supported image format) of external dependencies +# to the given file (report RP0402 must not be disabled). +ext-import-graph= + +# Output a graph (.gv or any supported image format) of all (i.e. internal and +# external) dependencies to the given file (report RP0402 must not be +# disabled). +import-graph= + +# Output a graph (.gv or any supported image format) of internal dependencies +# to the given file (report RP0402 must not be disabled). +int-import-graph= + +# Force import order to recognize a module as part of the standard +# compatibility libraries. +known-standard-library= + +# Force import order to recognize a module as part of a third party library. +known-third-party=enchant + +# Couples of modules and preferred modules, separated by a comma. +preferred-modules= + + +[LOGGING] + +# The type of string formatting that logging methods do. `old` means using % +# formatting, `new` is for `{}` formatting. +logging-format-style=old + +# Logging modules to check that the string format arguments are in logging +# function parameter format. +logging-modules=logging + + +[MESSAGES CONTROL] + +# Only show warnings with the listed confidence levels. Leave empty to show +# all. Valid levels: HIGH, CONTROL_FLOW, INFERENCE, INFERENCE_FAILURE, +# UNDEFINED. +confidence=HIGH, + CONTROL_FLOW, + INFERENCE, + INFERENCE_FAILURE, + UNDEFINED + +# Disable the message, report, category or checker with the given id(s). You +# can either give multiple identifiers separated by comma (,) or put this +# option multiple times (only on the command line, not in the configuration +# file where it should appear only once). You can also use "--disable=all" to +# disable everything first and then re-enable specific checks. For example, if +# you want to run only the similarities checker, you can use "--disable=all +# --enable=similarities". If you want to run only the classes checker, but have +# no Warning level messages displayed, use "--disable=all --enable=classes +# --disable=W". +disable=raw-checker-failed, + bad-inline-option, + locally-disabled, + file-ignored, + suppressed-message, + useless-suppression, + deprecated-pragma, + use-symbolic-message-instead, + use-implicit-booleaness-not-comparison-to-string, + use-implicit-booleaness-not-comparison-to-zero, + magic-value-comparison, + consider-alternative-union-syntax, + deprecated-typing-alias, + consider-using-assignment-expr, + import-outside-toplevel, + redefined-outer-name, + docstring-first-line-empty, + too-many-try-statements, + wrong-import-position, + too-few-public-methods, + too-many-positional-arguments, + too-many-arguments, + too-many-locals, + too-many-branches, + too-many-statements, + too-many-instance-attributes, + too-many-public-methods, + f-string-without-interpolation, + too-complex, + protected-access, + broad-exception-caught, + unspecified-encoding, + implicit-str-concat, + attribute-defined-outside-init, + duplicate-code, + missing-function-docstring, + missing-module-docstring, + missing-class-docstring, + line-too-long, + bare-except, + unnecessary-lambda-assignment, + eval-used, + exec-used, + global-statement, + invalid-name, + unused-argument, + cyclic-import + +# Enable the message, report, category or checker with the given id(s). You can +# either give multiple identifier separated by comma (,) or put this option +# multiple time (only on the command line, not in the configuration file where +# it should appear only once). See also the "--disable" option for examples. +enable= + +[METHOD_ARGS] + +# List of qualified names (i.e., library.method) which require a timeout +# parameter e.g. 'requests.api.get,requests.api.post' +timeout-methods=requests.api.delete,requests.api.get,requests.api.head,requests.api.options,requests.api.patch,requests.api.post,requests.api.put,requests.api.request + + +[MISCELLANEOUS] + +# List of note tags to take in consideration, separated by a comma. +notes=FIXME, + TODO, + XXX + +# Regular expression of note tags to take in consideration. +notes-rgx= + + +[REFACTORING] + +# Maximum number of nested blocks for function / method body +max-nested-blocks=5 + +# Complete name of functions that never returns. When checking for +# inconsistent-return-statements if a never returning function is called then +# it will be considered as an explicit return statement and no message will be +# printed. +never-returning-functions=sys.exit,argparse.parse_error + + +[REPORTS] + +# Python expression which should return a score less than or equal to 10. You +# have access to the variables 'fatal', 'error', 'warning', 'refactor', +# 'convention', and 'info' which contain the number of messages in each +# category, as well as 'statement' which is the total number of statements +# analyzed. This score is used by the global evaluation report (RP0004). +evaluation=max(0, 0 if fatal else 10.0 - ((float(5 * error + warning + refactor + convention) / statement) * 10)) + +# Template used to display messages. This is a python new-style format string +# used to format the message information. See doc for all details. +msg-template= + +# Set the output format. Available formats are: text, parseable, colorized, +# json2 (improved json format), json (old json format) and msvs (visual +# studio). You can also give a reporter class, e.g. +# mypackage.mymodule.MyReporterClass. +#output-format= + +# Tells whether to display a full report or only the messages. +reports=no + +# Activate the evaluation score. +score=yes + + +[SIMILARITIES] + +# Comments are removed from the similarity computation +ignore-comments=yes + +# Docstrings are removed from the similarity computation +ignore-docstrings=yes + +# Imports are removed from the similarity computation +ignore-imports=yes + +# Signatures are removed from the similarity computation +ignore-signatures=yes + +# Minimum lines number of a similarity. +min-similarity-lines=4 + + +[SPELLING] + +# Limits count of emitted suggestions for spelling mistakes. +max-spelling-suggestions=4 + +# Spelling dictionary name. No available dictionaries : You need to install +# both the python package and the system dependency for enchant to work. +spelling-dict= + +# List of comma separated words that should be considered directives if they +# appear at the beginning of a comment and should not be checked. +spelling-ignore-comment-directives=fmt: on,fmt: off,noqa:,noqa,nosec,isort:skip,mypy: + +# List of comma separated words that should not be checked. +spelling-ignore-words= + +# A path to a file that contains the private dictionary; one word per line. +spelling-private-dict-file= + +# Tells whether to store unknown words to the private dictionary (see the +# --spelling-private-dict-file option) instead of raising a message. +spelling-store-unknown-words=no + + +[STRING] + +# This flag controls whether inconsistent-quotes generates a warning when the +# character used as a quote delimiter is used inconsistently within a module. +check-quote-consistency=no + +# This flag controls whether the implicit-str-concat should generate a warning +# on implicit string concatenation in sequences defined over several lines. +check-str-concat-over-line-jumps=no + + +[TYPECHECK] + +# List of decorators that produce context managers, such as +# contextlib.contextmanager. Add to this list to register other decorators that +# produce valid context managers. +contextmanager-decorators=contextlib.contextmanager + +# List of members which are set dynamically and missed by pylint inference +# system, and so shouldn't trigger E1101 when accessed. Python regular +# expressions are accepted. +generated-members= + +# Tells whether to warn about missing members when the owner of the attribute +# is inferred to be None. +ignore-none=yes + +# This flag controls whether pylint should warn about no-member and similar +# checks whenever an opaque object is returned when inferring. The inference +# can return multiple potential results while evaluating a Python object, but +# some branches might not be evaluated, which results in partial inference. In +# that case, it might be useful to still emit no-member and other checks for +# the rest of the inferred objects. +ignore-on-opaque-inference=yes + +# List of symbolic message names to ignore for Mixin members. +ignored-checks-for-mixins=no-member, + not-async-context-manager, + not-context-manager, + attribute-defined-outside-init + +# List of class names for which member attributes should not be checked (useful +# for classes with dynamically set attributes). This supports the use of +# qualified names. +ignored-classes=optparse.Values,thread._local,_thread._local,argparse.Namespace + +# Show a hint with possible names when a member name was not found. The aspect +# of finding the hint is based on edit distance. +missing-member-hint=yes + +# The minimum edit distance a name should have in order to be considered a +# similar match for a missing member name. +missing-member-hint-distance=1 + +# The total number of similar names that should be taken in consideration when +# showing a hint for a missing member. +missing-member-max-choices=1 + +# Regex pattern to define which classes are considered mixins. +mixin-class-rgx=.*[Mm]ixin + +# List of decorators that change the signature of a decorated function. +signature-mutators= + + +[VARIABLES] + +# List of additional names supposed to be defined in builtins. Remember that +# you should avoid defining new builtins when possible. +additional-builtins= + +# Tells whether unused global variables should be treated as a violation. +allow-global-unused-variables=yes + +# List of names allowed to shadow builtins +allowed-redefined-builtins= + +# List of strings which can identify a callback function by name. A callback +# name must start or end with one of those strings. +callbacks=cb_, + _cb + +# A regular expression matching the name of dummy variables (i.e. expected to +# not be used). +dummy-variables-rgx=_+$|(_[a-zA-Z0-9_]*[a-zA-Z0-9]+?$)|dummy|^ignored_|^unused_ + +# Argument names that match this expression will be ignored. +ignored-argument-names=_.*|^ignored_|^unused_ + +# Tells whether we should check for unused import in __init__ files. +init-import=no + +# List of qualified module names which can have objects that can redefine +# builtins. +redefining-builtins-modules=six.moves,past.builtins,future.builtins,builtins,io \ No newline at end of file diff --git a/.secrets.baseline b/.secrets.baseline new file mode 100644 index 0000000..fe1cef1 --- /dev/null +++ b/.secrets.baseline @@ -0,0 +1,137 @@ +{ + "version": "1.5.0", + "plugins_used": [ + { + "name": "ArtifactoryDetector" + }, + { + "name": "AWSKeyDetector" + }, + { + "name": "AzureStorageKeyDetector" + }, + { + "name": "Base64HighEntropyString", + "limit": 4.5 + }, + { + "name": "BasicAuthDetector" + }, + { + "name": "CloudantDetector" + }, + { + "name": "DiscordBotTokenDetector" + }, + { + "name": "GitHubTokenDetector" + }, + { + "name": "GitLabTokenDetector" + }, + { + "name": "HexHighEntropyString", + "limit": 3.0 + }, + { + "name": "IbmCloudIamDetector" + }, + { + "name": "IbmCosHmacDetector" + }, + { + "name": "IPPublicDetector" + }, + { + "name": "JwtTokenDetector" + }, + { + "name": "KeywordDetector", + "keyword_exclude": "" + }, + { + "name": "MailchimpDetector" + }, + { + "name": "NpmDetector" + }, + { + "name": "OpenAIDetector" + }, + { + "name": "PrivateKeyDetector" + }, + { + "name": "PypiTokenDetector" + }, + { + "name": "SendGridDetector" + }, + { + "name": "SlackDetector" + }, + { + "name": "SoftlayerDetector" + }, + { + "name": "SquareOAuthDetector" + }, + { + "name": "StripeDetector" + }, + { + "name": "TelegramBotTokenDetector" + }, + { + "name": "TwilioKeyDetector" + } + ], + "filters_used": [ + { + "path": "detect_secrets.filters.allowlist.is_line_allowlisted" + }, + { + "path": "detect_secrets.filters.common.is_baseline_file", + "filename": ".secrets.baseline" + }, + { + "path": "detect_secrets.filters.common.is_ignored_due_to_verification_policies", + "min_level": 2 + }, + { + "path": "detect_secrets.filters.heuristic.is_indirect_reference" + }, + { + "path": "detect_secrets.filters.heuristic.is_likely_id_string" + }, + { + "path": "detect_secrets.filters.heuristic.is_lock_file" + }, + { + "path": "detect_secrets.filters.heuristic.is_not_alphanumeric_string" + }, + { + "path": "detect_secrets.filters.heuristic.is_potential_uuid" + }, + { + "path": "detect_secrets.filters.heuristic.is_prefixed_with_dollar_sign" + }, + { + "path": "detect_secrets.filters.heuristic.is_sequential_string" + }, + { + "path": "detect_secrets.filters.heuristic.is_swagger_file" + }, + { + "path": "detect_secrets.filters.heuristic.is_templated_secret" + }, + { + "path": "detect_secrets.filters.regex.should_exclude_file", + "pattern": [ + "\\.ipynb$" + ] + } + ], + "results": {}, + "generated_at": "2026-04-29T17:00:49Z" +} diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..b9b1854 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2026 Trillium Technologies Ltd. + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/README.md b/README.md index 9f81967..388e4e7 100644 --- a/README.md +++ b/README.md @@ -1,49 +1,75 @@ -# GEE MCP Server +# GEE MCP -This is a standalone Model Context Protocol (MCP) server for Google Earth Engine (GEE). It provides tools for dataset discovery, metadata extraction, and executing GEE Python code. +[![CI](https://github.com/FrontierDevelopmentLab/gee-mcp/actions/workflows/main.yml/badge.svg)](https://github.com/FrontierDevelopmentLab/gee-mcp/actions/workflows/main.yml) +[![Python](https://img.shields.io/badge/python-3.11%20%7C%203.12%20%7C%203.13%20%7C%203.14-blue)](https://github.com/FrontierDevelopmentLab/gee-mcp) +[![License: MIT](https://img.shields.io/badge/license-MIT-green)](LICENSE) -## Project Structure +An [MCP](https://modelcontextprotocol.io/) server that exposes +[Google Earth Engine](https://earthengine.google.com/) (GEE) as a set +of MCP tools — dataset discovery, metadata extraction, analysis +primitives, and AI-assisted GEE Python code generation. -- `server/`: The MCP server package. -- `client.py`: An example MCP client to test the server. -- `requirements.txt`: List of dependencies. +> **Status: alpha (v0.0.1) — work in progress.** APIs, tool names, and +> wire formats may change without notice. Not yet recommended for +> production use. -## Available Tools +## Tools -The server exposes several Model Context Protocol (MCP) tools categorised by their function: +The server registers the following MCP tools, grouped by purpose. ### Catalogue & Metadata -- `list_datasets`: List all available Google Earth Engine datasets. -- `get_dataset_info`: Get detailed Markdown information about a specific GEE dataset. -- `get_dataset_metadata`: Get structured STAC metadata (bands, temporal interval, etc.) for a dataset. -- `check_imagery_availability`: Check imagery availability for a dataset within a date range and optional bounding box. -- `extract_metadata`: Extract structured metadata (bands, pixel size, availability, cadence) from a dataset page. -- `analyze_metadata`: Use Gemini AI to analyse a dataset description and extract structured metadata. +- `list_datasets` — list all available Google Earth Engine datasets. +- `get_dataset_info` — get detailed Markdown information about a GEE + dataset. +- `get_dataset_metadata` — get structured STAC metadata (bands, + temporal interval, etc.) for a dataset. +- `check_imagery_availability` — check imagery availability for a + dataset within a date range and optional bounding box. +- `extract_metadata` — extract structured metadata (bands, pixel + size, availability, cadence) from a dataset page. +- `analyze_metadata` — use Gemini to analyse a dataset description + and extract structured metadata. ### Analysis & Data Processing -- `download_satellite_image`: Download satellite images from GEE. -- `compute_index`: Compute a spectral index (e.g., NDVI, NDWI) or custom band math expression over a region. -- `zonal_statistics`: Compute summary statistics (mean, median, min, etc.) for bands or an index within a region. -- `temporal_composite`: Create cloud-free temporal composites (median, mosaic, greenest, etc.). -- `mask_by_raster`: Apply a value-range mask (e.g., DEM, land cover) to imagery and compute statistics. -- `threshold_area`: Compute the area of pixels meeting a threshold condition on a band, index, or expression. -- `multi_period_analysis`: Run the same analysis across multiple date ranges for temporal comparisons. -- `execute_gee_python`: Execute a provided GEE Python script and return the result. +- `download_satellite_image` — download satellite images from GEE. +- `compute_index` — compute a spectral index (NDVI, NDWI, …) or a + custom band-math expression over a region. +- `zonal_statistics` — compute summary statistics (mean, median, + min, …) for bands or an index within a region. +- `temporal_composite` — create cloud-free temporal composites + (median, mosaic, greenest, most recent). +- `mask_by_raster` — apply a value-range mask (DEM, land cover, …) + to imagery and compute statistics. +- `threshold_area` — compute the area of pixels meeting a threshold + condition on a band, index, or expression. +- `multi_period_analysis` — run the same analysis across multiple + date ranges for temporal comparisons. +- `execute_gee_python` — execute a provided GEE Python script and + return the result. ### AI Code Generation & Validation -- `generate_python_from_question`: Answer an Earth Observation question by generating GEE Python code with iterative error fixing. -- `generate_abstract_graph_from_question`: Generate an abstract graph (Mermaid) describing an EO pipeline to solve a question. -- `generate_python_from_reasoning_steps`: Generate GEE Python code based on a provided set of reasoning steps. -- `generate_python_from_abstract_graph`: Generate GEE Python code based on a provided Mermaid graph. -- `get_datasets_locations_and_periods`: Determine the GEE datasets, time periods, and AOIs required to answer a given question. -- `extract_factuality_issues`: Analyze GEE Python script and extract data/scientific assumptions that might require factual verification. -- `assess_factuality_issue`: Assess one of the factuality issies extracted in the previous function call, and generate recommendations and code change suggestions. -- `identify_sensible_variables`: Identify variables and constants in the GEE Python code whose values might impact the final result. -- `sensitivity_analysis`: Perform sensitivity analysis by tweaking variable values in the code and plotting the impacts on the final result. - -## Example Tool Invocation - -Here is an example of how an MCP client might format a JSON-RPC request to invoke the `generate_python_from_question` tool: +- `generate_python_from_question` — answer an Earth Observation + question by generating GEE Python code with iterative error fixing. +- `generate_abstract_graph_from_question` — generate an abstract + Mermaid graph describing an EO pipeline that solves a question. +- `generate_python_from_reasoning_steps` — generate GEE Python code + from a provided set of reasoning steps. +- `generate_python_from_abstract_graph` — generate GEE Python code + from a provided Mermaid graph. +- `get_datasets_locations_and_periods` — determine the GEE datasets, + time periods, and AOIs required to answer a question. +- `extract_factuality_issues` — analyse a GEE Python script and + surface scientific assumptions worth verifying. +- `assess_factuality_issue` — produce an expert-style assessment of + a factuality issue, with optional code-fix recommendations. +- `identify_sensible_variables` — identify variables and constants + in the code whose values might affect the final result. +- `sensitivity_analysis` — perform sensitivity analysis by tweaking + variable values and plotting the impact on the final result. + +## Example tool invocation + +A JSON-RPC call to `generate_python_from_question` looks like: ```json { @@ -58,157 +84,130 @@ Here is an example of how an MCP client might format a JSON-RPC request to invok } ``` -It returns a json structure with several objects, most notably - -- `python_code`: the actual GEE Python code generated -- `python_code_explanation`: an explanation of the code generated -- `python_code_fix_history`: the iterative fixes made to the code -- `python_code_result`: the result after executing the code - -This is the code generated - -```python -import ee -import geemap - -def gee_main(): - # Define a point within the Amazon basin (near Manaus, Brazil) to intersect the basin polygon - amazon_point = ee.Geometry.Point([-60.0, -3.0]) - - # Load the WWF HydroATLAS Level 3 Basins dataset - # We use level 3 which contains the major continental basins like the Amazon - basins = ee.FeatureCollection('WWF/HydroATLAS/v1/Basins/level03') - amazon_basin = basins.filterBounds(amazon_point) - - # Load MODIS monthly NDVI data for the year 2023 - modis_ndvi = ee.ImageCollection('MODIS/061/MOD13A3') \ - .filterDate('2023-01-01', '2024-01-01') \ - .select('NDVI') - - # Calculate the mean NDVI image over the year and apply the scaling factor of 0.0001 - mean_ndvi_image = modis_ndvi.mean().multiply(0.0001) - - # Calculate the average NDVI over the entire Amazon basin - stats = mean_ndvi_image.reduceRegion( - reducer=ee.Reducer.mean(), - geometry=amazon_basin.geometry(), - scale=1000, # Matches the 1km resolution of MOD13A3 - maxPixels=1e12 - ) - - # Extract the average NDVI value - avg_ndvi = stats.get('NDVI').getInfo() - - # Initialize a geemap Map for visualization - Map = geemap.Map() - Map.centerObject(amazon_basin, 4) - - # Define NDVI visualization parameters - ndvi_vis = { - 'min': 0.0, - 'max': 1.0, - 'palette': [ - 'FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901', - '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01', - '012E01', '011D01', '011301' - ] - } - - # Add the layers to the map - Map.addLayer(amazon_basin.style(**{'fillColor': '00000000', 'color': 'FF0000'}), {}, 'Amazon Basin Boundary') - Map.addLayer(mean_ndvi_image.clip(amazon_basin), ndvi_vis, 'Mean NDVI 2023') - - # Format the result as an XML string - result_xml = f""" -average_ndvi -{avg_ndvi} -dimensionless -""" - - return result_xml, Map - ``` - -and this is the result when running the generated code (also done by the tool call itself) - -```xml - -average_ndvi -0.7712281332887203 -dimensionless - -``` +The response includes: -Observe that the generated code also returns a `Map` object so that it can be displayed in appropriate environments, such as IPython Notebookes. For instance, for this question +- `python_code` — the generated GEE Python code, +- `python_code_explanation` — an explanation of the code, +- `python_code_fix_history` — the iterative fixes attempted, +- `python_code_result` — the result of executing the code. -_Characterize the morphometry and land cover of the Emme catchment in the Canton of Bern by determining its total area, maximum elevation, and forest cover percentage. Additionally, state the financial magnitude of the damages caused by the flash flood event in this catchment (specifically in Schangnau) during July 2014._ +The generated code defines `gee_main()` returning `(result_xml, Map)`, +where `result_xml` follows a `... +......` shape, +and `Map` is a `geemap.Map` for notebook display. -the generated code returns the following answer and map: +## Installation -![map](imgs/gee-execution.png) +The project uses [Poetry](https://python-poetry.org/). -## Integration +```bash +git clone https://github.com/FrontierDevelopmentLab/gee-mcp.git +cd gee-mcp +poetry install +``` -As any other MCP server GEE MCP can be integrated in any agentic tool. For instance in Gemini-CLI +Supported Python versions: 3.11–3.14. -![geminicli](imgs/geminicli.png) +## Configuration +You need to configure access to **Gemini** and to **Google Earth +Engine** via environment variables. Copy [`.env.example`](.env.example) +to `.env` and fill in the values; `python-dotenv` is loaded on server +startup. -## Installation +### Gemini -Install dependencies: +Either set an API key: -```bash -pip install -r requirements.txt -``` +| Variable | Required | Purpose | +| --- | --- | --- | +| `GEMINI_API_KEY` or `GOOGLE_API_KEY` | yes (one of the two) | Gemini API key | + +…or use a Vertex AI project (after running `gcloud auth +application-default login`): -Ensure you have authenticated with Google Earth Engine and your environment is set up. +| Variable | Required | Default | Purpose | +| --- | --- | --- | --- | +| `VERTEXAI_PROJECT` | yes | — | GCP project ID for Vertex AI | +| `VERTEXAI_LOCATION` | no | `global` | GCP region for Vertex AI | -## Environment Variables +### Google Earth Engine -You need to set up access to Gemini (via an api key or a vertex ai project) and to Google Earth Engine. +| Variable | Required | Purpose | +| --- | --- | --- | +| `GEE_PROJECT` | yes | GEE project ID | +| `GOOGLE_APPLICATION_CREDENTIALS` | no | Path to a service-account JSON key file. Only needed if you have not authenticated via `earthengine authenticate` or `gcloud`. | +| `GEE_SKIP_AUTH` | no | Set to `1` to skip auth entirely (used by the test suite). | -### Access to Gemini +Authentication is delegated to `ee.Initialize`, which walks the +standard Google Cloud credential chain. Either run `earthengine +authenticate` (interactive, once per machine) or set +`GOOGLE_APPLICATION_CREDENTIALS` to a service-account key path. On +GCE / Cloud Run, instance metadata is picked up automatically. -You must set up either +## Running the server -- `GEMINI_API_KEY` or `GOOGLE_API_KEY`: for the Gemini API key +Over stdio (the standard MCP transport): -or, for a Vertex AI project +```bash +poetry run python -m gee_mcp.server +``` -- `VERTEXAI_PROJECT` (optional): The GCP project ID for Vertex AI (used if no API key is provided). -- `VERTEXAI_LOCATION` (optional): The GCP region for Vertex AI (defaults to `"global"`). +## Testing with the example client -assuming you have authenticated within that project via +The repo includes `client.py`, an example MCP client that launches +the server as a subprocess. ```bash -gcloud auth application-default login +poetry run python client.py ``` -### Access to Google Earth Engine +See `example.ipynb` for a notebook walk-through. -You must set +## Integration -- `GEE_PROJECT`: The GEE project id (required by `auth.py`). +GEE MCP can be plugged into any MCP-aware agent. For example, in +Gemini-CLI: +![geminicli](imgs/geminicli.png) -having previously authenticated via +For the question: -```bash -earthengine authenticate -``` +> Characterize the morphometry and land cover of the Emme catchment +> in the Canton of Bern by determining its total area, maximum +> elevation, and forest cover percentage. Additionally, state the +> financial magnitude of the damages caused by the flash flood event +> in this catchment (specifically in Schangnau) during July 2014. -## Running the Server +the generated code returns: -You can run the server via stdio (as a module): +![map](imgs/gee-execution.png) + +## Development + +Install the pre-commit hooks once: ```bash -python -m server +poetry run pre-commit install ``` -## Testing with Client +Run the full hook suite (detect-secrets, autoflake, black, isort, +mypy, pylint, pytest+coverage): -You can run the example client to test connection and tools: +```bash +poetry run pre-commit run --all-files +``` + +Run just the tests: ```bash -python client.py +poetry run pytest ``` + +## Acknowledgements + +Originally created by [Raúl Ramos](https://github.com/rramosp). + +## License + +MIT — see [LICENSE](LICENSE). diff --git a/client.py b/client.py index 5e7e390..69d3671 100644 --- a/client.py +++ b/client.py @@ -3,20 +3,22 @@ from __future__ import annotations import json +import os +import sys from types import TracebackType from typing import Any from mcp import ClientSession, StdioServerParameters from mcp.client.stdio import stdio_client -import sys PYTHON_BIN = sys.executable -SERVER_MODULE = "server" -import os +SERVER_MODULE = "gee_mcp.server" + class GEEToolError(RuntimeError): """Raised when the MCP server returns an error for a tool call.""" + class GEEMCPClient: """Async context manager wrapping an MCP stdio session. @@ -32,10 +34,20 @@ def __init__(self) -> None: self._cm_session: object = None async def __aenter__(self) -> GEEMCPClient: + # Prepend the local ``src/`` directory to PYTHONPATH so the + # example client can launch the server straight from a + # checkout (without installing the package first). + repo_src = os.path.join( + os.path.dirname(os.path.abspath(__file__)), "src" + ) + existing = os.environ.get("PYTHONPATH", "") + pythonpath = ( + f"{repo_src}{os.pathsep}{existing}" if existing else repo_src + ) params = StdioServerParameters( command=PYTHON_BIN, args=["-m", SERVER_MODULE], - env={**os.environ, "PYTHONPATH": os.path.dirname(os.path.abspath(__file__))}, + env={**os.environ, "PYTHONPATH": pythonpath}, ) self._cm_stdio = stdio_client(params) read, write = await self._cm_stdio.__aenter__() # type: ignore[union-attr] @@ -60,23 +72,20 @@ async def __aexit__( ) self._session = None - @staticmethod def _parse_result(result: Any) -> Any: """Extract JSON from a tool result, raising on server errors.""" text = result.content[0].text if result.isError: raise GEEToolError(text) - + try: return json.loads(text) except: return text - - async def test(self) -> str: - return {'test': 'uno'} - + async def test(self) -> dict: + return {"test": "uno"} async def get_metadata(self, catalog_id: str) -> dict: """Call ``get_dataset_metadata`` on the MCP server.""" @@ -111,57 +120,75 @@ async def check_availability( async def list_datasets(self) -> dict: """Call ``get_dataset_metadata`` on the MCP server.""" assert self._session is not None, "Use as async context manager" - result = await self._session.call_tool("list_datasets",{}) + result = await self._session.call_tool("list_datasets", {}) return self._parse_result(result) - async def generate_python_from_question(self, - question: str, - gee_datasets: list[dict] = None, - fix_code: bool = True) -> dict: + async def generate_python_from_question( + self, + question: str, + gee_datasets: list[dict] = None, + fix_code: bool = True, + ) -> dict: """Call ``generate_python_from_question`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( - "generate_python_from_question", - {"question": question, "gee_datasets": gee_datasets, 'fix_code': fix_code} + "generate_python_from_question", + { + "question": question, + "gee_datasets": gee_datasets, + "fix_code": fix_code, + }, ) return self._parse_result(result) - async def generate_abstract_graph_from_question(self, - question: str, - gee_datasets: list[dict] = None) -> dict: + async def generate_abstract_graph_from_question( + self, question: str, gee_datasets: list[dict] = None + ) -> dict: """Call ``generate_abstract_graph_from_question`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( - "generate_abstract_graph_from_question", - {"question": question, "gee_datasets": gee_datasets} + "generate_abstract_graph_from_question", + {"question": question, "gee_datasets": gee_datasets}, ) return self._parse_result(result) - async def generate_python_from_reasoning_steps(self, - question: str, - reasoning_steps: str, - gee_datasets: list[dict] = None, - fix_code: bool = True) -> dict: - + async def generate_python_from_reasoning_steps( + self, + question: str, + reasoning_steps: str, + gee_datasets: list[dict] = None, + fix_code: bool = True, + ) -> dict: """Call ``generate_python_from_reasoning_steps`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( - "generate_python_from_reasoning_steps", - {"question": question, "gee_datasets": gee_datasets, 'reasoning_steps': reasoning_steps, 'fix_code': fix_code} + "generate_python_from_reasoning_steps", + { + "question": question, + "gee_datasets": gee_datasets, + "reasoning_steps": reasoning_steps, + "fix_code": fix_code, + }, ) return self._parse_result(result) - async def generate_python_from_abstract_graph(self, - question: str, - abstract_graph: str, - gee_datasets: list = None, - fix_code: bool = True) -> dict: - + async def generate_python_from_abstract_graph( + self, + question: str, + abstract_graph: str, + gee_datasets: list = None, + fix_code: bool = True, + ) -> dict: """Call ``generate_python_from_abstract_graph`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( - "generate_python_from_abstract_graph", - {"question": question, "gee_datasets": gee_datasets, 'abstract_graph': abstract_graph, 'fix_code': fix_code} + "generate_python_from_abstract_graph", + { + "question": question, + "gee_datasets": gee_datasets, + "abstract_graph": abstract_graph, + "fix_code": fix_code, + }, ) return self._parse_result(result) @@ -169,45 +196,58 @@ async def execute_gee_python(self, code: str) -> dict: """Call ``execute_gee_python`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( - "execute_gee_python", - {"code": code} + "execute_gee_python", {"code": code} ) return self._parse_result(result) - async def extract_factuality_issues(self, question: str, python_code: str) -> dict: + async def extract_factuality_issues( + self, question: str, python_code: str + ) -> dict: """Call ``extract_factuality_issues`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( "extract_factuality_issues", - {"question": question, "python_code": python_code} + {"question": question, "python_code": python_code}, ) return self._parse_result(result) - async def get_datasets_locations_and_periods(self, question: str, gee_datasets: list[dict]) -> dict: + async def get_datasets_locations_and_periods( + self, question: str, gee_datasets: list[dict] + ) -> dict: """Call ``get_datasets_locations_and_periods`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( "get_datasets_locations_and_periods", - {"question": question, "gee_datasets": gee_datasets} + {"question": question, "gee_datasets": gee_datasets}, ) return self._parse_result(result) - async def identify_sensible_variables(self, question: str, python_code: str, baseline_answer: str) -> list[dict]: + async def identify_sensible_variables( + self, question: str, python_code: str, baseline_answer: str + ) -> list[dict]: """Call ``identify_sensible_variables`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( "identify_sensible_variables", - {"question": question, "python_code": python_code, 'baseline_answer':baseline_answer} + { + "question": question, + "python_code": python_code, + "baseline_answer": baseline_answer, + }, ) return self._parse_result(result) - - async def sensitivity_analysis(self, question: str, python_code: str, baseline_answer: str) -> list[dict]: + async def sensitivity_analysis( + self, question: str, python_code: str, baseline_answer: str + ) -> list[dict]: """Call ``sensitivity_analysis`` on the MCP server.""" assert self._session is not None, "Use as async context manager" result = await self._session.call_tool( "sensitivity_analysis", - {"question": question, "python_code": python_code, 'baseline_answer':baseline_answer} + { + "question": question, + "python_code": python_code, + "baseline_answer": baseline_answer, + }, ) return self._parse_result(result) - diff --git a/example.ipynb b/example.ipynb index cfcfb37..bb1ac70 100644 --- a/example.ipynb +++ b/example.ipynb @@ -14,14 +14,14 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "32e0076d-1cc3-4e5c-be15-8af8540e5ee1", "metadata": {}, "outputs": [], "source": [ "import os\n", - "os.environ['GEE_PROJECT']='ee-raulramos' # your Google Earth Engine project\n", - "os.environ['VERTEXAI_PROJECT']='genai-dev-454121' # your VertexAI GCP project\n", + "os.environ['GEE_PROJECT']='your-gee-project' # your Google Earth Engine project\n", + "os.environ['VERTEXAI_PROJECT']='your-vertexai-project' # your VertexAI GCP project\n", "\n", "import asyncio\n", "from client import GEEMCPClient\n" @@ -32,15 +32,7 @@ "execution_count": null, "id": "43bb3e11", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Listing datasets...\n" - ] - } - ], + "outputs": [], "source": [ "async def run_example():\n", " async with GEEMCPClient() as client:\n", @@ -79,20 +71,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "2fe0a65b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Executing GEE Python code...\n", - "Execution Result: {'result': {'type': 'Point', 'coordinates': [-122.45, 37.75]}}\n" - ] - } - ], + "outputs": [], "source": [ "async def run_code_example():\n", " async with GEEMCPClient() as client:\n", @@ -125,21 +107,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "dbe1276b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Cloud Percentage around Barcelona in Jan-Feb 2024: 13.18%\n", - "Total Area: 1241.62 km²\n", - "Cloud Area: 163.70 km²\n", - "\\nTile URL for Map Visualization retrieved.\n" - ] - } - ], + "outputs": [], "source": [ "async def run_advanced_example():\n", " async with GEEMCPClient() as client:\n", @@ -199,8 +170,8 @@ " else:\n", " data = res['result']\n", " print(f\"Cloud Percentage around Barcelona in Jan-Feb 2024: {data['cloud_percentage']:.2f}%\")\n", - " print(f\"Total Area: {data['total_area_km2']:.2f} km²\")\n", - " print(f\"Cloud Area: {data['cloud_area_km2']:.2f} km²\")\n", + " print(f\"Total Area: {data['total_area_km2']:.2f} km\u00b2\")\n", + " print(f\"Cloud Area: {data['cloud_area_km2']:.2f} km\u00b2\")\n", " print(f\"\\\\nTile URL for Map Visualization retrieved.\")\n", " return data['tile_url']\n", "\n", @@ -209,163 +180,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "4f33e98b", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
Make this Notebook Trusted to load map: File -> Trust Notebook
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"Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Programming Language :: Python :: 3.14", + "Programming Language :: Python :: 3 :: Only", +] + + +[tool.poetry.dependencies] +python = "^3.11" +mcp = "^1.26.0" +fastmcp = "^3.1.0" +earthengine-api = ">=1.0.0" +requests = "^2.31" +beautifulsoup4 = "^4.12" +markitdown = "*" +loguru = "^0.7" +pandas = "*" +numpy = "*" +matplotlib = "*" +python-dotenv = "^1.0" +google-genai = "*" +pydantic = "^2.0" + + +[tool.poetry.group.dev.dependencies] +pre-commit = "^4.5.1" +autoflake = "^2.2.1" +isort = "^5.13.2" +black = "^23.3.0" +mypy = "^1.8.0" +pylint = "^3.2.0" +coverage = "^7.4.1" +pytest = ">=8.0.0" +pytest-asyncio = ">=0.23.0" +pytest-cov = ">=4.0.0" +pytest-testdox = "^3.1.0" +pytest-mock = "^3.14.0" +detect-secrets = "^1.5.0" +pytest-env = "^1.1.5" +pylint-per-file-ignores = "^3.2.0" + +[tool.black] +line-length = 79 +target-version = ['py311', 'py312'] +include = '\.pyi?$' +extend-exclude = ''' +/( + | blib2to3 + | tests/data + | profiling + | \.git + | __pycache__ + | \.tox + | \venv + | \.venv +)/ +''' + +[tool.isort] +profile = "black" +line_length = 79 +skip_glob = [ + '*.parquet', +] +filter_files = true +skip_gitignore = true + +[tool.mypy] +exclude = [ + '\.yaml$', + '\.yml$', + '\.toml$', + '\.venv', +] +ignore_missing_imports = true + +# The GEE-heavy modules call into a typed-but-incomplete external API +# (earthengine-api). Skip strict type-checking on those; types in the +# small pure-Python modules (helpers, models, app, config) still get +# checked. +[[tool.mypy.overrides]] +module = [ + "gee_mcp.server.tools_analysis", + "gee_mcp.server.tools_catalogue", + "gee_mcp.server.tools_execution", + "gee_mcp.server.analysis", + "gee_mcp.server.codegen", + "gee_mcp.server.coderun", + "gee_mcp.server.helpers", + "gee_mcp.server.utils", + "gee_mcp.server.genai", + "gee_mcp.server.auth", + "gee_mcp.server.models", +] +ignore_errors = true + +[tool.pytest.ini_options] +pythonpath = [ + "src" +] +asyncio_mode = "auto" +asyncio_default_fixture_loop_scope = "function" +testpaths = ["tests"] +addopts = "-v --tb=short --basetemp=/tmp/pytest" + +[tool.coverage.run] +source = ["src"] +omit = ["tests/**/conftest.py", "tests/*"] +data_file = "/tmp/gee_mcp/.coverage" + +[tool.coverage.report] +exclude_also = [ + "def __repr__", + "if self\\.debug", + "if DEBUG_PRINT:", + "if DEBUG_PRINTS:", + "raise AssertionError", + "raise NotImplementedError", + "if 0:", + "if __name__ == .__main__.:", + "@(abc\\.)?abstractmethod", + ] +ignore_errors = true + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index de18b37..0000000 --- a/requirements.txt +++ /dev/null @@ -1,10 +0,0 @@ -fastmcp -earthengine-api -requests -beautifulsoup4 -markitdown -loguru -pandas -numpy -mermaid-py -python-dotenv diff --git a/server.log b/server.log deleted file mode 100644 index a05e6f8..0000000 --- a/server.log +++ /dev/null @@ -1,7 +0,0 @@ -2026-04-01 08:03:55,757 - SERVER - INFO - HTTP Request: GET https://pypi.org/pypi/fastmcp/json "HTTP/1.1 200 OK" -2026-04-01 08:03:56,035 - SERVER - INFO - Starting worker 'raulramos#904593' with the following tasks: -2026-04-01 08:03:56,038 - SERVER - INFO - * trace(message: str, ...) -2026-04-01 08:03:56,038 - SERVER - INFO - * fail(message: str, ...) -2026-04-01 08:03:56,039 - SERVER - INFO - * sleep(seconds: float, ...) -2026-04-01 08:03:56,081 - SERVER - INFO - Processing request of type CallToolRequest -2026-04-01 08:04:06,316 - SERVER - INFO - Processing request of type ListToolsRequest diff --git a/server/__main__.py b/server/__main__.py deleted file mode 100644 index 20d7052..0000000 --- a/server/__main__.py +++ /dev/null @@ -1,5 +0,0 @@ -"""Entry point for ``python -m server``.""" - -from .app import mcp - -mcp.run(transport="stdio") diff --git a/server/app.py b/server/app.py deleted file mode 100644 index cbfca46..0000000 --- a/server/app.py +++ /dev/null @@ -1,19 +0,0 @@ -"""FastMCP application instance and logging configuration.""" - -import logging -import os - -from fastmcp import FastMCP - -log_file_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), "server.log") -logging.basicConfig( - level=logging.INFO, - format="%(asctime)s - SERVER - %(levelname)s - %(message)s", - handlers=[ - logging.FileHandler(log_file_path, mode="w"), - logging.StreamHandler(), - ], - force=True, -) - -mcp = FastMCP("mcp-gee-server") diff --git a/server/auth.py b/server/auth.py deleted file mode 100644 index 6654514..0000000 --- a/server/auth.py +++ /dev/null @@ -1,137 +0,0 @@ -"""Shared GEE authentication module. - -Implements a 4-level fallback chain: - 1. gee-key.json service account file - 2. Environment variables (GEE_SERVICE_ACCOUNT + key path) - 3. Default user credentials - 4. Interactive gcloud authentication -""" - -import json -import logging -import os - -import ee -from dotenv import load_dotenv - -load_dotenv() - -logger = logging.getLogger(__name__) - - -def setup_gee(key_path: str | None = None) -> None: - """Authenticate and initialise the Earth Engine API. - - Tries four methods in order, stopping at the first success: - - 1. **Service-account key file** — uses *key_path* if provided, otherwise - looks for ``/.config/geo-stars-2fc6f2e84e4e.json``. - 2. **Environment variables** — uses ``GEE_SERVICE_ACCOUNT`` (or - ``EE_SERVICE_ACCOUNT``) together with ``GEE_PRIVATE_KEY_PATH`` (or - ``GOOGLE_APPLICATION_CREDENTIALS``). - 3. **Default user credentials** — calls ``ee.Initialize()`` with no - explicit credentials (works when already authenticated via gcloud). - 4. **Interactive gcloud auth** — runs ``ee.Authenticate()`` as a last - resort (controlled by ``GEE_AUTH_MODE``, default ``"gcloud"``). - - All methods use ``GEE_PROJECT`` for the GEE project id. If the key file - (level 1) is found, the project id is read from it as a fallback. - - :param key_path: optional path to a GEE service-account JSON key file. - When provided this is tried first, skipping the default key location. - :raises RuntimeError: if all four methods fail. - """ - gee_project = os.getenv("GEE_PROJECT") - logger.debug("GEE auth: GEE_PROJECT=%s", gee_project or "(not set)") - - # --- Level 1: service-account key file ------------------------------ - # Walk upward from the current file's directory looking for .config/ - _search = os.path.dirname(os.path.abspath(__file__)) - key_path = None - subdirs = [".config", "env"] - for _ in range(4): - for subdir in subdirs: - candidate = os.path.join( - _search, subdir, "geo-stars-2fc6f2e84e4e.json" - ) - if os.path.exists(candidate): - key_path = os.path.abspath(candidate) - break - _search = os.path.dirname(_search) - logger.debug("GEE auth [1/4]: looking for key file %s", key_path) - if key_path and os.path.exists(key_path): - try: - with open(key_path) as f: - key_data = json.load(f) - project = gee_project or key_data.get("project_id") - sa_email = key_data.get("client_email", "?") - logger.debug( - "GEE auth [1/4]: found key file, service account=%s, project=%s", - sa_email, project, - ) - if not project: - raise ValueError( - "GEE project ID not found in key file or GEE_PROJECT env var." - ) - credentials = ee.ServiceAccountCredentials(sa_email, key_path) - ee.Initialize(credentials, project=project) - logger.debug("GEE auth [1/4]: success (service-account key file)") - return - except Exception as e: - logger.warning("GEE auth [1/4]: failed: %s", e) - else: - logger.debug("GEE auth [1/4]: key file not found, skipping") - - # --- Level 2: environment variables --------------------------------- - service_account = os.getenv("GEE_SERVICE_ACCOUNT") or os.getenv( - "GEE_SERVICE_ACCOUNT" - ) - env_key_path = os.getenv("GEE_PRIVATE_KEY_PATH") or os.getenv( - "GOOGLE_APPLICATION_CREDENTIALS" - ) - logger.debug( - "GEE auth [2/4]: env vars: service_account=%s, key_path=%s", - service_account or "(not set)", env_key_path or "(not set)", - ) - if not gee_project: - raise RuntimeError( - "GEE_PROJECT is not set and key file failed or was not found." - ) - if service_account and env_key_path and os.path.exists(env_key_path): - try: - logger.debug( - "GEE auth [2/4]: trying service account %s with key %s", - service_account, env_key_path, - ) - credentials = ee.ServiceAccountCredentials( - service_account, env_key_path - ) - ee.Initialize(credentials, project=gee_project) - logger.debug("GEE auth [2/4]: success (env-var service account)") - return - except Exception as e: - logger.warning("GEE auth [2/4]: failed: %s", e) - else: - logger.debug("GEE auth [2/4]: incomplete env vars, skipping") - - # --- Level 3: default user credentials ------------------------------ - logger.debug("GEE auth [3/4]: trying default credentials, project=%s", gee_project) - try: - ee.Initialize(project=gee_project) - logger.debug("GEE auth [3/4]: success (default user credentials)") - return - except Exception as e: - logger.warning("GEE auth [3/4]: failed: %s", e) - - # --- Level 4: interactive gcloud auth ------------------------------- - auth_mode = os.getenv("GEE_AUTH_MODE", "gcloud") - logger.debug("GEE auth [4/4]: trying interactive auth (mode=%s)", auth_mode) - try: - ee.Authenticate(auth_mode=auth_mode) - ee.Initialize(project=gee_project) - logger.debug("GEE auth [4/4]: success (interactive %s)", auth_mode) - except Exception as e: - raise RuntimeError( - "All GEE authentication methods failed. " - f"Last error: {e}" - ) from e diff --git a/server/utils.py b/server/utils.py deleted file mode 100644 index 3bb7b5a..0000000 --- a/server/utils.py +++ /dev/null @@ -1,538 +0,0 @@ -import json -import re -import pandas as pd -import numpy as np -from datetime import datetime, timezone - -from .helpers import extract_xml_tag, extract_tag -import ee -from loguru import logger - - -def extract_dataset_metadata(t: str): - """ - Extracts metadata from a markdown string representation of a GEE dataset page. - - Args: - t (str): The markdown content of the dataset page. - - Returns: - dict: A dictionary containing the extracted metadata, including - the following keys: 'data' (a dataframe), 'pixel_size', 'availability_start_date', 'availability_end_date', and 'cadence'. - """ - - i = 0 - r = [] - ti = t[:] - - # Parse the markdown to identify sections based on headers - while True: - i = ti.find("\n#") - if i == -1: - break - name = ti[i : i + ti[i + 1 :].find("\n") + 1] - ti = ti[i + len(name) + 1 :][:] - - # Calculate the position of the section in the original text - position = t.find(ti) - len(name) - - level = name.count("#") - name = name.replace("\n", "").replace("#", "").strip() - - r.append( - {"section": name, "header_level": level, "position": position} - ) - - # Extract content for each section - for i in range(len(r)): - a = r[i]["position"] - b = r[i + 1]["position"] if i < len(r) - 1 else -1 - r[i]["content"] = t[a:b] - - r = pd.DataFrame(r) - - # extract pixel size - pixel_size = None - if "bands" in r.section.str.lower().values: - ri = r[r.section.str.lower() == "bands"].iloc[0] - m = re.search( - r"\*\*pixel size\*\*(.*?)\*\*bands", - ri.content.lower(), - flags=re.DOTALL, - ) - if m: - pixel_size = m.group(1).strip() - - # extract availability dates - availability_start_date, availability_end_date = None, None - if "page summary" in r.section.str.lower().values: - ri = r[r.section.str.lower() == "page summary"].iloc[0] - m = re.search( - r"dataset availability(\s+):(.*?)\n\n", - ri.content.lower(), - flags=re.DOTALL, - ) - if m: - dataset_availability = " ".join(m.groups()).strip() - availability_start_date, availability_end_date = ( - dataset_availability.split("–") - ) - - # extract cadence - cadence = None - if "page summary" in r.section.str.lower().values: - ri = r[r.section.str.lower() == "page summary"].iloc[0] - m = re.search( - r"\ncadence(\s+):(.*?)\n\n", ri.content.lower(), flags=re.DOTALL - ) - if m: - cadence = " ".join(m.groups()).strip() - - return { - "data": r, - "pixel_size": pixel_size, - "availability_start_date": availability_start_date, - "availability_end_date": availability_end_date, - "cadence": cadence, - } - - -def analyze_dataset_metadata(genai, t): - """ - Uses a Generative AI model to analyze and extract structured metadata from a dataset description. - - This function constructs a prompt containing the dataset description and instructions - for the AI to extract specific fields like ID, description, availability, pixel size, - cadence, bands, and potential applications. - - Args: - genai: The Generative AI client object used to generate the response. - t (str): The raw text or markdown description of the dataset. - - Returns: - str: A JSON-formatted string containing the extracted metadata. - """ - - # Construct the prompt with instructions for the model to extract metadata - prompt = f""" - - You are an expert extractor of information from earth observation metadata. - This is the description of an earth observation dataset in Google Earth Engine. - - - {t} - - - Your tasks are: - - the dataset id - - compile a detailed description of the dataset - - extract the availability start date and end date of the dataset - - extract the pixel size of the different bands of the dataset - - extract the cadence or time resolution of the dataset - - extract a list of bands with all the data associated - - infer a list of possible applications for this dataset. - - Take into consideration the following aspects: - - - some datasets have a single, global pixel size, whilst others have different pixel - sizes for different bands. In either case extract a list of all pixel sizes - present in the dataset. - - - bands usually come described in a table with different fields like band name, - pixel size, description, value ranges, etc. Extract them all. - - - sometimes cadence might not be explicitly stated in the dataset. If this is the case - try to infer it from the full description. - - Provide your answer as a json structre such as this one: - - - {{ - "dataset_id": "COPERNICUS_S1_GRD", - "description": "this dataset contains ....", - "applications": this dataset could be used to ....", - "availability_start": "2020-01-01T00:00:00Z", - "availability_end": "2026-01-31T06:00:00Z", - "pixel_size": [ "10 meters", "60 meters" ], - "cadence": "6 hours" - "bands": [ {{"name": "B1", "description": "coastal aerosol", "pixel_size": "10 meters", "wavelength": " 0.43 - 0.45 μm"}}, - {{"name": "B2", "description": "green", "pixel_size": "60 meters", "wavelength": " 0.46 - 0.50 μm"}} - }} - - """ - - # Call the AI model to generate the response - response = genai.call(prompt) - return response - - -def timestamp_to_datetime(ts: int) -> datetime: - """ - Converts a unix timestamp in seconds, milliseconds, microseconds, or nanoseconds - to a datetime object. Assumes timezone is UTC. - """ - - if ts > 1e18: - return datetime.fromtimestamp(ts / 1e9, tz=timezone.utc) # nanoseconds - elif ts > 1e15: - return datetime.fromtimestamp( - ts / 1e6, tz=timezone.utc - ) # microseconds - elif ts > 1e12: - return datetime.fromtimestamp( - ts / 1e3, tz=timezone.utc - ) # milliseconds - else: - return datetime.fromtimestamp(ts, tz=timezone.utc) # seconds - - - - -def distribute_points(a, b, x, n): - """ - Distributes n points within (a, b) given an existing point x - to maximize the minimum distance between all points. - """ - if not (a < x < b): - raise ValueError("x must be within the interval (a, b)") - - # Calculate the total length and the proportion of n points for each side - total_length = b - a - left_ratio = (x - a) / total_length - - # Estimate how many points should go to the left of x - n_left = round(left_ratio * n) - n_right = n - n_left - - # Generate points for the left segment (a, x) - # We use n_left + 1 spaces - left_points = [a + (i + 1) * (x - a) / (n_left + 1) for i in range(n_left)] - - # Generate points for the right segment (x, b) - # We use n_right + 1 spaces - right_points = [x + (i + 1) * (b - x) / (n_right + 1) for i in range(n_right)] - - # Combine and return sorted list - return sorted(left_points + right_points) - -def extract_standardized_numeric_answer(text): - - ex = [] - - pattern = r"(.*?)" - - results = re.findall(pattern, text, flags=re.DOTALL) - - # Clean up and print - for i, match in enumerate(results, 1): - ss = match.strip() - value = extract_xml_tag(ss, 'VALUE') - - # attempt to convert to float - try: - value = float(value) - except: - pass - ex.append({ - 'answer_field_name': extract_xml_tag(ss, 'VARIABLE_NAME'), - 'answer_field_value': value, - 'answer_field_units': extract_xml_tag(ss, 'UNITS'), - - }) - - return ex - -def extract_numeric_answer(genai_client, question, answer): - prompt = f""" - You are an expert in Earth Observation. You are given an Earth Observation question - and a verbose answer to it. - - Your task is to extract the fields and their numeric values from the answer that are - relevant to answering the question. - - Your answer should be a list of json structures each one having two entries 'answer_field_name' - and 'answer_field_value', such as in this example output - - [{{'answer_field_name': 'ndvi difference', 'answer_field_value': -0.4012}} ] - - This is the question - - {question} - - - And this is the answer - - {answer} - - - """ - r = genai_client.call(prompt) - - return json.loads(extract_tag(r['answer'], 'json')) - - -def extract_field_meaning(genai_client, question, answer): - prompt = f""" - You are an expert in Earth Observation. You are given an Earth Observation question - and a verbose answer to it. - - Your task is to extract the fields and their meanings that are - relevant to answering the question. - - Your answer should be a list of json structures each one having two entries 'answer_field_name' - and 'answer_field_meaning', such as in this example output - - [{{'answer_field_name': 'ndvi difference', 'answer_field_meaning': 'The difference in NDVI values between two time periods'}} ] - - This is the question - - {question} - - - And this is the answer - - {answer} - - - """ - r = genai_client.call(prompt) - - return json.loads(extract_tag(r['answer'], 'json')) - - -class ParameterSensitivity: - """ - Sensitivity analysis of Google Earth Engine Python code for Earth Observation questions. - - First it identifies the variables and constants in the code that are most likely to affect the final result, - then it changes the value of each variable to a value for sensitivity analysis, executes the modified code, - - The change in value for sensitivity analysis is computed as the original value plus two thirds of the distance - to the maximum value. - - We compute the linear range impact in output variable as the relative change in output variable - divided by the relative change in value of the code variable, when changing the code variable - from its original value to the value for sensitivity analysis. - - See doc in run method below. - - :var guidelines: Description - """ - - - def __init__(self, genai_client, gee_client, question_record, n_samples_per_code_variable=3): - - self.genai_client = genai_client - self.question_record = question_record - self.gee_client = gee_client - - q = self.question_record - self.question = q["question"] - self.python_code = q['python_code'] - self.baseline_answer = q['python_code_result'] - self.input_variables = None - self.output_variables = None - self.sensitivity_results = None - self.n_samples_per_code_variable = n_samples_per_code_variable - - - def gee_identify_sensible_variables(self): - """ - identifies the variables and constants in the code that are most likely to affect the final result, - by calling genai with a prompt that includes the code and the question, and asking for a list of - variables and constants with their value range and an estimate of their impact on the final result. - - Then, for each variable, it generates a set of values for sensitivity analysis by distributing n - samples within the value range of the variable, given the original value of the variable, - to maximize the minimum distance between all points. The number of points n is defined in - self.n_samples_per_code_variable. - """ - - if self.input_variables is not None: - return self.input_variables - - logger.info('identifying sensible variables in code') - - prompt = f""" - You are an Earth Observation expert with excellent coding of the Google Earth Engine Python API. - - Your task is to analyze the following Google Earth Engine Python API Code and identify the - constants and variables which are most likely to affect its final result. The Python code - below provides an answer to the following Earth Observation question - - - {self.question} - - - Follow these guidelines: - - - Assume the spatial and temporal extents are corrent. Do not consider those in your analysis. - - - Consider only continuous numerical variables and constants, not categorical variables or variables with string values. - - - Assume as well that the overall processing pipeline is corrent, including the datasets - it uses. - - - For each variable you identify try to infer: - (1) a value range with its minimum and maximum values. - (2) what is the impact (LOW, MEDIUM, HIGH) you estimate that changes in this variable - will have on the final output when running the code, together with a justified - explanation of your estimate. - - - Provide a list of the names of the variables and constant values that you identify in a list - with json format like in this example: - - [ {{'name': 'threshold', 'value': 40, 'explanation': 'this variable holds the limit by which - pixels with buildinds are selected', 'value_range': (20,60), 'estimated_impact': 'LOW', - 'estimated_impact_justification': '......'}}, - {{'name': 'cloud_percentage', 'value': 20, 'explanation': 'this variable holds represents - the maximum clouding percentage admitted for the calculation', 'value_range': (0,100), - 'estimated_impact': 'HIGH', 'estimated_impact_justification': '.....'}} - ] - - - - {self.python_code} - - - - """ - - r = self.genai_client.call(prompt) - sensible_vars = eval(extract_tag(r['answer'], 'json')) - - s = pd.DataFrame(sensible_vars) - - - rs = [] - for _,si in s.iterrows(): - v = si['value'] - try: - vmin, vmax = eval(str(si.value_range)) - svals = distribute_points(vmin, vmax, v, self.n_samples_per_code_variable) - except Exception as e: - print (si.value_range, e) - vmin, vmax, svals = np.nan, np.nan, np.nan - rs.append({'vmin': vmin, 'vmax':vmax, 'values_for_sensitivity_analysis': svals}) - - rs = pd.DataFrame(rs, index=s.index) - s = s.join(rs) - s.index = s['name'] - self.input_variables = s - return s - - - def run(self): - """ - run sensitivity analysis by changing the value of each variable identified in - gee_identify_sensible_variables to the value for sensitivity analysis, and then - executing the modified code and extracting the answer. - - For each input variable (in the code) we do this self.n_samples_per_code_variable times, - changing the variable value to a different value for sensitivity analysis each time, - and extracting the answer each time. - - return: a dict with the sensitivity analysis results, with the following structure: - { - 'output_variable_1': { - 'input_variable_1': { - 'samples': [ - {'input': value_1, 'output': output_value_1}, is_baseline='yes'}, - {'input': value_2, 'output': output_value_2}, - ] - } - ... - } - ... - } - - is_baseline refers to the value_1 beding the original value of the variable in the original code, - and output_value_1 being the answer obtained when executing the original code with the - original variable value. - """ - s = self.gee_identify_sensible_variables() - - - logger.info('----- sensible variables identified in code') - logger.info(s['name'].values) - - sensitivity = {} - baseline = extract_standardized_numeric_answer(self.baseline_answer) - self.output_variables = extract_field_meaning(self.genai_client, self.question, self.baseline_answer) - - # copy units for metadata - for v in self.output_variables: - for b in baseline: - if b['answer_field_name'] == v['answer_field_name']: - v['answer_field_units'] = b['answer_field_units'] - - - for _, si in s.iterrows(): - variable_name = si['name'] - variable_values = si['values_for_sensitivity_analysis'] - - # add baseline - sensitivity[variable_name] = [{'value': si['value'], - 'is_baseline': 'yes', - 'output': baseline} ] - - logger.info('----') - logger.info(f"---- analyzing variable {variable_name} within estimated range {si['value_range']}") - for variable_value in variable_values: - - logger.info(f"---- changing {variable_name} value from {si['value']} to {variable_value:.4f}") - - if pd.isna(variable_value): - logger.info('skipping nan value') - continue - - - prompt = f""" - you are an expert Google Earth Engine Python code interpreter. - - your task is to modify the following Google Earth Engine Python code, so that - the variable named "{variable_name}" has value "{variable_value}" all throughout - the script. - - Output the fully modified code within and xml tags - - --- Python Google Earth Engine Code starts here --- - - {self.python_code} - - """ - - logger.info('modifying python code with new variable value') - r = self.genai_client.call(prompt) - - logger.info('executing new code') - python_modified = extract_xml_tag(r['answer'], 'MODIFIED_PYTHON') - rr = self.gee_client.exec(python_modified) - - logger.info('extracting answer') - #sensitivity[variable_name] = extract_numeric_answer(self.genai_client, self.question, rr[0]) - sensitivity[variable_name].append( {'value': variable_value, 'output': extract_standardized_numeric_answer(rr[0])} ) - - logger.info(f'new result {sensitivity[variable_name]}') - - - # store in case in error it can be used for debugging - self.sensitivity_results = sensitivity - # gather all data in a two-level dict with first key input var, and second key output var - ss = {} - for output_variable in self.output_variables: - output_variable = output_variable['answer_field_name'] - ss[output_variable] = {} - for input_variable in s['name'].values: - ssi = {} - ssi['samples'] = [{'input': i['value'], 'output': j['answer_field_value']} for i in sensitivity[input_variable] for j in i['output'] if j['answer_field_name'] == output_variable] - try: - ssi['baseline'] = {'input': si['value'], 'output': [i['answer_field_value'] for i in baseline if i['answer_field_name']==output_variable][0]} - except: - ssi['baseline'] = {'input': si['value'], 'output': np.nan} - ss[output_variable][input_variable] = ssi - - self.sensitivity_results = ss - - return ss - \ No newline at end of file diff --git a/src/gee_mcp/__init__.py b/src/gee_mcp/__init__.py new file mode 100644 index 0000000..b1041bf --- /dev/null +++ b/src/gee_mcp/__init__.py @@ -0,0 +1 @@ +"""GEE MCP server.""" diff --git a/src/gee_mcp/config.py b/src/gee_mcp/config.py new file mode 100644 index 0000000..00aed6f --- /dev/null +++ b/src/gee_mcp/config.py @@ -0,0 +1,3 @@ +"""Module-level configuration constants.""" + +SERVER_MODULE = "gee_mcp.server" diff --git a/server/__init__.py b/src/gee_mcp/server/__init__.py similarity index 87% rename from server/__init__.py rename to src/gee_mcp/server/__init__.py index 476f289..2f5d85a 100644 --- a/server/__init__.py +++ b/src/gee_mcp/server/__init__.py @@ -1,7 +1,6 @@ """Unified FastMCP server for GEE. -Registers all tools (download, dataset listing, metadata extraction/ -analysis) under a single ``FastMCP("mcp-gee-server")`` instance. +Registers all tools under a single ``FastMCP("gee-mcp")`` instance. Tools ----- @@ -21,8 +20,13 @@ - ``generate_python_from_question`` - ``generate_python_from_reasoning_steps`` - ``generate_python_from_abstract_graph`` -- ``generate_generate_abstract_graph_from_question`` +- ``generate_abstract_graph_from_question`` - ``extract_factuality_issues`` +- ``assess_factuality_issue`` +- ``get_datasets_locations_and_periods`` +- ``identify_sensible_variables`` +- ``sensitivity_analysis`` +- ``execute_gee_python`` Prompts ------- @@ -31,11 +35,9 @@ Run standalone:: - python -m server + python -m gee_mcp.server """ -import os - from .auth import setup_gee # ------------------------------------------------------------------ @@ -45,12 +47,23 @@ setup_gee() - # ------------------------------------------------------------------ # Re-export everything from submodules for convenience. # ------------------------------------------------------------------ +from .analysis import ( # noqa: E402, F401 + _extract_factuality_issues, + _get_datasets_locations_and_periods, + _identify_sensible_variables, + _sensitivity_analysis, +) from .app import mcp # noqa: E402 +from .codegen import ( # noqa: E402, F401 + _generate_abstract_graph_from_question, + _generate_python_from_abstract_graph, + _generate_python_from_question, + _generate_python_from_reasoning_steps, +) from .constants import ( # noqa: E402 _REDUCER_MAP, BASE_URL, @@ -92,8 +105,10 @@ _temporal_composite, _threshold_area, _zonal_statistics, + assess_factuality_issue, compute_index, download_satellite_image, + extract_factuality_issues, get_datasets_locations_and_periods, identify_sensible_variables, mask_by_raster, @@ -102,12 +117,6 @@ temporal_composite, threshold_area, zonal_statistics, - extract_factuality_issues, -) -from .analysis import ( # noqa: E402, F401 - _get_datasets_locations_and_periods, - _identify_sensible_variables, - _sensitivity_analysis, ) from .tools_catalogue import ( # noqa: E402, F401 _get_dataset_info, @@ -120,31 +129,12 @@ get_metadata_prompt, list_datasets, ) - from .tools_execution import ( # noqa: E402, F401 + execute_gee_python, + generate_abstract_graph_from_question, + generate_python_from_abstract_graph, generate_python_from_question, generate_python_from_reasoning_steps, - generate_python_from_abstract_graph, - generate_abstract_graph_from_question, - execute_gee_python -) - -from .codegen import ( # noqa: E402, F401 - _generate_python_from_question, - _generate_python_from_reasoning_steps, - _generate_python_from_abstract_graph, - _generate_abstract_graph_from_question, -) - -from .coderun import ( - _execute_gee_python -) - -from .analysis import ( - _extract_factuality_issues, - _get_datasets_locations_and_periods, - _identify_sensible_variables, - _sensitivity_analysis, ) # ------------------------------------------------------------------ diff --git a/src/gee_mcp/server/__main__.py b/src/gee_mcp/server/__main__.py new file mode 100644 index 0000000..0a05521 --- /dev/null +++ b/src/gee_mcp/server/__main__.py @@ -0,0 +1,12 @@ +"""Entry point for ``python -m gee_mcp.server``.""" + +from . import mcp + + +def main(): + """Run the MCP server over stdio.""" + mcp.run(transport="stdio") + + +if __name__ == "__main__": + main() diff --git a/server/analysis.py b/src/gee_mcp/server/analysis.py similarity index 65% rename from server/analysis.py rename to src/gee_mcp/server/analysis.py index 8097e71..31c7ffe 100644 --- a/server/analysis.py +++ b/src/gee_mcp/server/analysis.py @@ -1,24 +1,25 @@ -import re +import itertools import json -import pandas as pd +import re + +import matplotlib.pyplot as plt import numpy as np +import pandas as pd from loguru import logger -import itertools -import matplotlib.pyplot as plt -from .helpers import extract_tag, extract_xml_tag from .coderun import _execute_gee_python from .genai import init_genai_client +from .helpers import extract_tag, extract_xml_tag -def _get_datasets_locations_and_periods(question: str, - gee_datasets: list[dict] = None, - ) -> dict: - +def _get_datasets_locations_and_periods( + question: str, + gee_datasets: list[dict] = None, +) -> dict: genai_client = init_genai_client() - - dataset_instructions = f""" + dataset_instructions = ( + f""" We also know that the following datasets are the only ones available in Google Earth Engine @@ -27,7 +28,10 @@ def _get_datasets_locations_and_periods(question: str, - you must use one or more of the Google Earth Engine datasets - you do not need to use all the datasets in the list, but you can only use the ones in that list - """ if gee_datasets is not None else '' + """ + if gee_datasets is not None + else "" + ) prompt = f""" you are an expert data scientist specialized in earth observation datasets and, specifically, in Google @@ -73,15 +77,15 @@ def _get_datasets_locations_and_periods(question: str, """ - logger.debug('calling genai for extraction') - + logger.debug("calling genai for extraction") + r = genai_client.call(prompt) - r['json'] = json.loads(extract_tag(r['answer'], 'json')) - + r["json"] = json.loads(extract_tag(r["answer"], "json")) + return r -def _extract_factuality_issues(question: str, python_code: str) -> str: +def _extract_factuality_issues(question: str, python_code: str) -> str: genai_client = init_genai_client() prompt = f""" @@ -112,9 +116,10 @@ def _extract_factuality_issues(question: str, python_code: str) -> str: ] """ - logger.debug('calling genai to extract factuality issues') + logger.debug("calling genai to extract factuality issues") r = genai_client.call(prompt) - return extract_tag(r['answer'], 'json') + return extract_tag(r["answer"], "json") + def distribute_points(a, b, x, n): """ @@ -127,7 +132,7 @@ def distribute_points(a, b, x, n): # Calculate the total length and the proportion of n points for each side total_length = b - a left_ratio = (x - a) / total_length - + # Estimate how many points should go to the left of x n_left = round(left_ratio * n) n_right = n - n_left @@ -135,41 +140,45 @@ def distribute_points(a, b, x, n): # Generate points for the left segment (a, x) # We use n_left + 1 spaces left_points = [a + (i + 1) * (x - a) / (n_left + 1) for i in range(n_left)] - + # Generate points for the right segment (x, b) # We use n_right + 1 spaces - right_points = [x + (i + 1) * (b - x) / (n_right + 1) for i in range(n_right)] + right_points = [ + x + (i + 1) * (b - x) / (n_right + 1) for i in range(n_right) + ] # Combine and return sorted list return sorted(left_points + right_points) + def extract_standardized_numeric_answer(text): - ex = [] - + pattern = r"(.*?)" - + results = re.findall(pattern, text, flags=re.DOTALL) - + # Clean up and print for i, match in enumerate(results, 1): ss = match.strip() - value = extract_xml_tag(ss, 'VALUE') + value = extract_xml_tag(ss, "VALUE") # attempt to convert to float try: value = float(value) except: pass - ex.append({ - 'answer_field_name': extract_xml_tag(ss, 'VARIABLE_NAME'), - 'answer_field_value': value, - 'answer_field_units': extract_xml_tag(ss, 'UNITS'), - - }) + ex.append( + { + "answer_field_name": extract_xml_tag(ss, "VARIABLE_NAME"), + "answer_field_value": value, + "answer_field_units": extract_xml_tag(ss, "UNITS"), + } + ) return ex + def extract_numeric_answer(genai_client, question, answer): prompt = f""" You are an expert in Earth Observation. You are given an Earth Observation question @@ -196,7 +205,7 @@ def extract_numeric_answer(genai_client, question, answer): """ r = genai_client.call(prompt) - return json.loads(extract_tag(r['answer'], 'json')) + return json.loads(extract_tag(r["answer"], "json")) def extract_field_meaning(genai_client, question, answer): @@ -225,7 +234,7 @@ def extract_field_meaning(genai_client, question, answer): """ r = genai_client.call(prompt) - return json.loads(extract_tag(r['answer'], 'json')) + return json.loads(extract_tag(r["answer"], "json")) class SensitivityAnalizer: @@ -235,11 +244,11 @@ class SensitivityAnalizer: First it identifies the variables and constants in the code that are most likely to affect the final result, then it changes the value of each variable to a value for sensitivity analysis, executes the modified code, - The change in value for sensitivity analysis is computed as the original value plus two thirds of the distance + The change in value for sensitivity analysis is computed as the original value plus two thirds of the distance to the maximum value. - - We compute the linear range impact in output variable as the relative change in output variable - divided by the relative change in value of the code variable, when changing the code variable + + We compute the linear range impact in output variable as the relative change in output variable + divided by the relative change in value of the code variable, when changing the code variable from its original value to the value for sensitivity analysis. See doc in run method below. @@ -247,13 +256,16 @@ class SensitivityAnalizer: :var guidelines: Description """ - - def __init__(self, question, python_code, python_code_result, - n_samples_per_code_variable=3): - + def __init__( + self, + question, + python_code, + python_code_result, + n_samples_per_code_variable=3, + ): self.genai_client = init_genai_client() - self.question = question + self.question = question self.python_code = python_code self.baseline_answer = python_code_result self.input_variables = None @@ -261,23 +273,22 @@ def __init__(self, question, python_code, python_code_result, self.sensitivity_results = None self.n_samples_per_code_variable = n_samples_per_code_variable - def gee_identify_sensible_variables(self): """ - identifies the variables and constants in the code that are most likely to affect the final result, - by calling genai with a prompt that includes the code and the question, and asking for a list of + identifies the variables and constants in the code that are most likely to affect the final result, + by calling genai with a prompt that includes the code and the question, and asking for a list of variables and constants with their value range and an estimate of their impact on the final result. - Then, for each variable, it generates a set of values for sensitivity analysis by distributing n - samples within the value range of the variable, given the original value of the variable, - to maximize the minimum distance between all points. The number of points n is defined in + Then, for each variable, it generates a set of values for sensitivity analysis by distributing n + samples within the value range of the variable, given the original value of the variable, + to maximize the minimum distance between all points. The number of points n is defined in self.n_samples_per_code_variable. """ if self.input_variables is not None: return self.input_variables - logger.debug('identifying sensible variables in code') + logger.debug("identifying sensible variables in code") prompt = f""" You are an Earth Observation expert with excellent coding of the Google Earth Engine Python API. @@ -326,48 +337,54 @@ def gee_identify_sensible_variables(self): """ r = self.genai_client.call(prompt) - sensible_vars = eval(extract_tag(r['answer'], 'json')) + sensible_vars = eval(extract_tag(r["answer"], "json")) s = pd.DataFrame(sensible_vars) - rs = [] - for _,si in s.iterrows(): - v = si['value'] + for _, si in s.iterrows(): + v = si["value"] try: vmin, vmax = eval(str(si.value_range)) - svals = distribute_points(vmin, vmax, v, self.n_samples_per_code_variable) - if si['type'] == 'int': + svals = distribute_points( + vmin, vmax, v, self.n_samples_per_code_variable + ) + if si["type"] == "int": svals = [int(i) for i in svals] except Exception as e: - print (si.value_range, e) + print(si.value_range, e) vmin, vmax, svals = np.nan, np.nan, np.nan - rs.append({'vmin': vmin, 'vmax':vmax, 'values_for_sensitivity_analysis': svals}) + rs.append( + { + "vmin": vmin, + "vmax": vmax, + "values_for_sensitivity_analysis": svals, + } + ) rs = pd.DataFrame(rs, index=s.index) s = s.join(rs) - s.index = s['name'] + s.index = s["name"] self.input_variables = s return s - def run(self): """ - run sensitivity analysis by changing the value of each variable identified in - gee_identify_sensible_variables to the value for sensitivity analysis, and then + run sensitivity analysis by changing the value of each variable identified in + gee_identify_sensible_variables to the value for sensitivity analysis, and then executing the modified code and extracting the answer. - For each input variable (in the code) we do this self.n_samples_per_code_variable times, - changing the variable value to a different value for sensitivity analysis each time, + For each input variable (in the code) we do this self.n_samples_per_code_variable times, + changing the variable value to a different value for sensitivity analysis each time, and extracting the answer each time. - + return: a dict with the sensitivity analysis results, with the following structure: { 'output_variable_1': { 'input_variable_1': { 'samples': [ {'input': value_1, 'output': output_value_1}, is_baseline='yes'}, - {'input': value_2, 'output': output_value_2}, + {'input': value_2, 'output': output_value_2}, ] } ... @@ -375,50 +392,62 @@ def run(self): ... } - is_baseline refers to the value_1 beding the original value of the variable in the original code, - and output_value_1 being the answer obtained when executing the original code with the + is_baseline refers to the value_1 beding the original value of the variable in the original code, + and output_value_1 being the answer obtained when executing the original code with the original variable value. """ s = self.gee_identify_sensible_variables() - logger.info(f"sensible variables identified in code {s['name'].values}") + logger.info( + f"sensible variables identified in code {s['name'].values}" + ) sensitivity = {} baseline = extract_standardized_numeric_answer(self.baseline_answer) - self.output_variables = extract_field_meaning(self.genai_client, self.question, self.baseline_answer) + self.output_variables = extract_field_meaning( + self.genai_client, self.question, self.baseline_answer + ) # copy units for metadata for v in self.output_variables: for b in baseline: - if b['answer_field_name'] == v['answer_field_name']: - v['answer_field_units'] = b['answer_field_units'] - + if b["answer_field_name"] == v["answer_field_name"]: + v["answer_field_units"] = b["answer_field_units"] for _, si in s.iterrows(): - variable_name = si['name'] - variable_values = si['values_for_sensitivity_analysis'] + variable_name = si["name"] + variable_values = si["values_for_sensitivity_analysis"] # add baseline - sensitivity[variable_name] = [{'value': si['value'], - 'is_baseline': 'yes', - 'output': baseline} ] + sensitivity[variable_name] = [ + { + "value": si["value"], + "is_baseline": "yes", + "output": baseline, + } + ] - logger.info(f"analyzing variable {variable_name} within estimated range {si['value_range']}") + logger.info( + f"analyzing variable {variable_name} within estimated range {si['value_range']}" + ) try: variable_values = [float(i) for i in variable_values] - except Exception as e: - logger.warning(f"skipping '{variable_name}' as could not convert values {variable_values} to float") + except Exception: + logger.warning( + f"skipping '{variable_name}' as could not convert values {variable_values} to float" + ) continue for variable_value in variable_values: - - logger.debug(f"---- changing {variable_name} value from {si['value']} to {variable_value:.4f}") - + logger.debug( + f"---- changing {variable_name} value from {si['value']} to {variable_value:.4f}" + ) + if pd.isna(variable_value): - logger.debug('skipping nan value') + logger.debug("skipping nan value") continue - + prompt = f""" you are an expert Google Earth Engine Python code interpreter. @@ -433,19 +462,27 @@ def run(self): {self.python_code} """ - - logger.debug('modifying python code with new variable value') + + logger.debug("modifying python code with new variable value") r = self.genai_client.call(prompt) - - logger.debug('executing new code') - python_modified = extract_xml_tag(r['answer'], 'MODIFIED_PYTHON') + + logger.debug("executing new code") + python_modified = extract_xml_tag( + r["answer"], "MODIFIED_PYTHON" + ) rr = _execute_gee_python(python_modified) rr = json.loads(rr) - sensitivity[variable_name].append( {'value': variable_value, 'output': extract_standardized_numeric_answer(rr['result'])} ) - - logger.debug(f'new result {sensitivity[variable_name]}') + sensitivity[variable_name].append( + { + "value": variable_value, + "output": extract_standardized_numeric_answer( + rr["result"] + ), + } + ) + logger.debug(f"new result {sensitivity[variable_name]}") # store in case in error it can be used for debugging self.sensitivity_results = sensitivity @@ -453,67 +490,95 @@ def run(self): # gather all data in a two-level dict with first key input var, and second key output var ss = {} for output_variable in self.output_variables: - output_variable = output_variable['answer_field_name'] + output_variable = output_variable["answer_field_name"] ss[output_variable] = {} - for input_variable in s['name'].values: + for input_variable in s["name"].values: ssi = {} - ssi['samples'] = [{'input': i['value'], 'output': j['answer_field_value']} for i in sensitivity[input_variable] for j in i['output'] if j['answer_field_name'] == output_variable] + ssi["samples"] = [ + {"input": i["value"], "output": j["answer_field_value"]} + for i in sensitivity[input_variable] + for j in i["output"] + if j["answer_field_name"] == output_variable + ] try: - ssi['baseline'] = {'input': si['value'], 'output': [i['answer_field_value'] for i in baseline if i['answer_field_name']==output_variable][0]} + ssi["baseline"] = { + "input": si["value"], + "output": [ + i["answer_field_value"] + for i in baseline + if i["answer_field_name"] == output_variable + ][0], + } except: - ssi['baseline'] = {'input': si['value'], 'output': np.nan} + ssi["baseline"] = {"input": si["value"], "output": np.nan} ss[output_variable][input_variable] = ssi self.sensitivity_results = ss return ss - def get_analysis_summary(self): - + def get_analysis_summary(self): metadata_output_vars = self.output_variables metadata_input_vars = self.input_variables - + output_vars = list(self.sensitivity_results.keys()) input_vars = list(self.sensitivity_results[output_vars[0]].keys()) - + h, w = len(output_vars), len(input_vars) - fig, axs = plt.subplots(h, w, figsize=(w*4, h*3)) - + fig, axs = plt.subplots(h, w, figsize=(w * 4, h * 3)) + axs = axs.flatten() - - md = f'## question \n\n {self.question}\n\n' - md += '## output variables\n' + + md = f"## question \n\n {self.question}\n\n" + md += "## output variables\n" for metadata_output_var in metadata_output_vars: md += f"- **{metadata_output_var['answer_field_name']}** ({metadata_output_var['answer_field_units']}): {metadata_output_var['answer_field_meaning']}\n" - - md += '## input variables (in the code)\n' - for _,metadata_input_var in metadata_input_vars.iterrows(): - md += f"**{metadata_input_var.name}**:\n"\ - f"- **meaning**: {metadata_input_var.explanation}\n"\ - f"- **values range**: {metadata_input_var.value_range}\n"\ - f"- **estimated impact**: {metadata_input_var.estimated_impact}\n"\ - f"- **impact justification**: {metadata_input_var.estimated_impact_justification}\n\n" - - md += '\n## sensitivity with respect to variables in the code\n\n**output vars** in y-axes, **input vars** in x-axes' - for (output_var, input_var, ), ax in zip(itertools.product(output_vars, input_vars), axs): - - metadata_output_var = [i for i in metadata_output_vars if i['answer_field_name'] == output_var][0] - + md += "## input variables (in the code)\n" + for _, metadata_input_var in metadata_input_vars.iterrows(): + md += ( + f"**{metadata_input_var.name}**:\n" + f"- **meaning**: {metadata_input_var.explanation}\n" + f"- **values range**: {metadata_input_var.value_range}\n" + f"- **estimated impact**: {metadata_input_var.estimated_impact}\n" + f"- **impact justification**: {metadata_input_var.estimated_impact_justification}\n\n" + ) + + md += "\n## sensitivity with respect to variables in the code\n\n**output vars** in y-axes, **input vars** in x-axes" + + for ( + output_var, + input_var, + ), ax in zip(itertools.product(output_vars, input_vars), axs): + metadata_output_var = [ + i + for i in metadata_output_vars + if i["answer_field_name"] == output_var + ][0] + vv = self.sensitivity_results[output_var][input_var] - zz = pd.DataFrame(vv['samples']).sort_values(by='input', ascending=True) - - ax.plot(zz['input'], zz['output'], marker='o') + zz = pd.DataFrame(vv["samples"]).sort_values( + by="input", ascending=True + ) + + ax.plot(zz["input"], zz["output"], marker="o") if input_var == input_vars[0]: - ax.set_ylabel(f"OUTPUT\n{output_var} ({metadata_output_var['answer_field_units']})") - ax.set_xlabel(f'INPUT {input_var}') + ax.set_ylabel( + f"OUTPUT\n{output_var} ({metadata_output_var['answer_field_units']})" + ) + ax.set_xlabel(f"INPUT {input_var}") ax.grid() - - #ax.set_title(f"OUTPUT\n{output_var} ({metadata_output_var['answer_field_units']})") - - + + # ax.set_title(f"OUTPUT\n{output_var} ({metadata_output_var['answer_field_units']})") + # set uniform output range - all_outputs = np.r_[[ii['output'] for i in self.sensitivity_results[output_var].values() for ii in i['samples']]] + all_outputs = np.r_[ + [ + ii["output"] + for i in self.sensitivity_results[output_var].values() + for ii in i["samples"] + ] + ] try: omin, omax = all_outputs.min(), all_outputs.max() vmin = omin - (omax - omin) * 0.05 @@ -521,93 +586,59 @@ def get_analysis_summary(self): ax.set_ylim(vmin, vmax) except: # in case of categorical variables, there is no max or min - pass - + pass + fig.tight_layout() - import io import base64 + import io + strbytes = io.BytesIO() - fig.savefig(strbytes, format='jpg') + fig.savefig(strbytes, format="jpg") strbytes.seek(0) img_b64 = base64.b64encode(strbytes.read()).decode() - md = f'{md}\n\n![Hello World](data:image/png;base64,{img_b64})' + md = f"{md}\n\n![Hello World](data:image/png;base64,{img_b64})" return md # functions for direct calling with strings -def _sensitivity_analysis(question: str, - python_code: str, - baseline_answer: str) -> str: - - rs = SensitivityAnalizer(question=question, - python_code=python_code, - python_code_result=baseline_answer) +def _sensitivity_analysis( + question: str, python_code: str, baseline_answer: str +) -> str: + rs = SensitivityAnalizer( + question=question, + python_code=python_code, + python_code_result=baseline_answer, + ) rs.run() markdown_answer = rs.get_analysis_summary() return markdown_answer -def _identify_sensible_variables(question: str, - python_code: str, - baseline_answer: str) -> str: - - rs = SensitivityAnalizer(question=question, - python_code=python_code, - python_code_result=baseline_answer) +def _identify_sensible_variables( + question: str, python_code: str, baseline_answer: str +) -> str: + rs = SensitivityAnalizer( + question=question, + python_code=python_code, + python_code_result=baseline_answer, + ) rs.run() - result = [i.to_json() for _m,i in rs.input_variables.iterrows()] + result = [i.to_json() for _m, i in rs.input_variables.iterrows()] return result -def _extract_factuality_issues(question: str, python_code: str) -> str: - - from .genai import init_genai_client - - genai_client = init_genai_client() - - prompt = f""" - You are a helpful assistant for Earth Observation data analysis with Google Earth Engine. - The Python code below was devised to answer the following question - - - {question} - - - Your task is to analyze the Google Earth Engine Python code below and extract what aspects - or issues are making scientific or data assumptions either explicitly or implicitly and might require - factual verification. - - - {python_code} - - - Your response must be a list of json structures, each one describing a specific aspect you identify - and containing the following fields: - [ - {{"title": "A short title describing the aspect or assumption", - "description": "A detailed description of the aspect or assumption, why it might require factual verification", - "facts": "Data, information, constants or facts to be verified", - "question_for_expert": "The question that should be posed to an expert to verify the aspect or assumption" - }} - {{ ... more issues ...}} - ] - - """ - logger.info('calling genai to extract factuality issues') - r = genai_client.call(prompt) - return extract_tag(r['answer'], 'json') - - -async def _assess_factuality_issue(question: str, - python_code: str, - issue_title: str, - issue_description: str, - issue_facts: str, - issue_question_for_expert: str) -> str: +async def _assess_factuality_issue( + question: str, + python_code: str, + issue_title: str, + issue_description: str, + issue_facts: str, + issue_question_for_expert: str, +) -> str: prompt = f""" I am trying solve the following Earth Observation question @@ -656,10 +687,9 @@ async def _assess_factuality_issue(question: str, genai_client = init_genai_client() r = genai_client.call(prompt) - code_recommendations = extract_xml_tag(r['answer'], 'CODE_RECOMMENDATIONS') - if '```json' in code_recommendations: - code_recommendations = extract_tag(code_recommendations, 'json') - r['answer'] = r['answer'].replace(code_recommendations, '') - r.update({'code_recommendations': code_recommendations}) + code_recommendations = extract_xml_tag(r["answer"], "CODE_RECOMMENDATIONS") + if "```json" in code_recommendations: + code_recommendations = extract_tag(code_recommendations, "json") + r["answer"] = r["answer"].replace(code_recommendations, "") + r.update({"code_recommendations": code_recommendations}) return json.dumps(r) -~ diff --git a/src/gee_mcp/server/app.py b/src/gee_mcp/server/app.py new file mode 100644 index 0000000..7451314 --- /dev/null +++ b/src/gee_mcp/server/app.py @@ -0,0 +1,5 @@ +"""FastMCP application instance.""" + +from fastmcp import FastMCP + +mcp = FastMCP("gee-mcp") diff --git a/src/gee_mcp/server/auth.py b/src/gee_mcp/server/auth.py new file mode 100644 index 0000000..1b25edc --- /dev/null +++ b/src/gee_mcp/server/auth.py @@ -0,0 +1,38 @@ +"""Google Earth Engine initialisation. + +Auth resolution is delegated to ``ee.Initialize``, which walks the +standard Google Cloud credential chain: + + - ``GOOGLE_APPLICATION_CREDENTIALS`` (service-account key JSON) + - gcloud Application Default Credentials cache + - The persistent EE credentials from ``earthengine authenticate`` + - GCE / Cloud Run instance metadata +""" + +import logging +import os + +import ee +from dotenv import load_dotenv + +load_dotenv() + +logger = logging.getLogger(__name__) + + +def setup_gee() -> None: + """Initialise the Earth Engine API for ``GEE_PROJECT``. + + Honours ``GEE_SKIP_AUTH=1`` as a no-op escape hatch (used by the + test suite). Otherwise requires ``GEE_PROJECT`` and lets + ``ee.Initialize`` resolve credentials from the standard GCP chain. + """ + if os.getenv("GEE_SKIP_AUTH") == "1": + logger.debug("GEE auth: skipped (GEE_SKIP_AUTH=1)") + return + + project = os.getenv("GEE_PROJECT") + if not project: + raise RuntimeError("GEE_PROJECT environment variable is required.") + ee.Initialize(project=project) + logger.debug("Earth Engine initialised for project %s", project) diff --git a/server/codegen.py b/src/gee_mcp/server/codegen.py similarity index 60% rename from server/codegen.py rename to src/gee_mcp/server/codegen.py index 56bc520..ad7f493 100644 --- a/server/codegen.py +++ b/src/gee_mcp/server/codegen.py @@ -1,63 +1,67 @@ -import re -import mermaid as md -from loguru import logger -from glob import glob import json -import numpy as np import os -import ee -from .helpers import extract_tag, extract_xml_tag, remove_leading_spaces, NoTagFoundError +from glob import glob + +import numpy as np +from loguru import logger + +from .coderun import GEEPythonExecution from .genai import init_genai_client -from .coderun import GEEPythonExecution +from .helpers import ( + NoTagFoundError, + extract_tag, + extract_xml_tag, + remove_leading_spaces, +) + class QuestionRecord: """ class to manage EO questions and associated artifacts (graph, generated code, etc.) """ + @classmethod def load_question(cls, question_file): with open(question_file) as f: q = json.load(f) - if 'graph' in q.keys(): - q['graph_javascript'] = q['graph'] - del(q['graph']) + if "graph" in q.keys(): + q["graph_javascript"] = q["graph"] + del q["graph"] - if 'graph_fixed' in q.keys(): - q['graph_javascript_fixed'] = q['graph_fixed'] - del(q['graph_fixed']) + if "graph_fixed" in q.keys(): + q["graph_javascript_fixed"] = q["graph_fixed"] + del q["graph_fixed"] - if 'explanation' in q.keys(): - q['explanation_javascript'] = q['explanation'] - del(q['explanation']) + if "explanation" in q.keys(): + q["explanation_javascript"] = q["explanation"] + del q["explanation"] - if 'thinking' in q.keys(): - q['thiking_python'] = q['thinking'] - del(q['thinking']) + if "thinking" in q.keys(): + q["thinking_python"] = q["thinking"] + del q["thinking"] + + dataset_dir = "/".join(question_file.split("/")[:-1]) + + qo = cls( + question=q["question"], dataset_dir=dataset_dir, exists_ok=True + ) + if "remarks" in q.keys(): + qo.remarks_for_prompts = q["remarks"] - dataset_dir = '/'.join(question_file.split('/')[:-1]) - - qo = cls(question=q['question'], dataset_dir=dataset_dir, exists_ok=True) - if 'remarks' in q.keys(): - qo.remarks_for_prompts = q['remarks'] - qo.record = q qo.question_file = question_file - if 'reference_refined_question' in qo.record.keys(): - - s = qo.record['reference_refined_question']['steps'] - s = "\n - "+"\n - ".join([i['sub_question'] for i in s]) + if "reference_refined_question" in qo.record.keys(): + s = qo.record["reference_refined_question"]["steps"] + s = "\n - " + "\n - ".join([i["sub_question"] for i in s]) - qo.record['reasoning_steps'] = s + qo.record["reasoning_steps"] = s - return qo + return qo - def __init__(self, - question, - dataset_dir=None, - exists_ok=False): + def __init__(self, question, dataset_dir=None, exists_ok=False): """ if 'dataset_dir' is None, nothing will be saved (useful for transient calls) """ @@ -67,27 +71,31 @@ def __init__(self, if dataset_dir is not None: r = self.check_question_exists() - + if not exists_ok: if r: - raise ValueError(f'question already exists in {r}') + raise ValueError(f"question already exists in {r}") else: self.question_file = r - self.record = {'question': self.question} + self.record = {"question": self.question} def clean(self): for k in list(self.record.keys()): - if k not in ['question', 'reference_refined_question', 'reasoning_steps']: - del(self.record[k]) + if k not in [ + "question", + "reference_refined_question", + "reasoning_steps", + ]: + del self.record[k] return self - def __setitem__(self, k,v): + def __setitem__(self, k, v): self.record[k] = v def __getitem__(self, k): return self.record[k] - + def keys(self): return self.record.keys() @@ -98,27 +106,27 @@ def check_question_exists(self): # checks if the question already exists in any of the entries # in the dataset (checks q*.json files under dataset_dir) q = remove_leading_spaces(self.question) - q = self.question.replace('\n', ' ').strip() + q = self.question.replace("\n", " ").strip() - files = glob(f'{self.dataset_dir}/q*.json') + files = glob(f"{self.dataset_dir}/q*.json") for file in files: with open(file) as f: - qj = json.load(f)['question'] + qj = json.load(f)["question"] qj = remove_leading_spaces(qj) - qj = qj.replace('\n', ' ').strip() + qj = qj.replace("\n", " ").strip() if q == qj: return file - - return False + + return False def set_question_file(self, question_file): self.question_file = question_file return self def save(self): - """ saves dict 'r' under 'dataset_dir' as qNNNN.json - with a consecutive number wrt the files already - existing in the folder + """saves dict 'r' under 'dataset_dir' as qNNNN.json + with a consecutive number wrt the files already + existing in the folder """ # skip if no dataset dir provided @@ -127,38 +135,43 @@ def save(self): if self.question_file is not None: if os.path.isfile(self.question_file): - logger.info(f'saving record in existing file {self.question_file}') + logger.info( + f"saving record in existing file {self.question_file}" + ) else: - logger.info(f'saving record in new file {self.question_file}') - with open(self.question_file, 'w') as f: + logger.info(f"saving record in new file {self.question_file}") + with open(self.question_file, "w") as f: json.dump(self.record, f, indent=4) return # if question file is not set, create a consecutive number file - files = glob(f'{self.dataset_dir}/q*.json') - if len(files)==0: + files = glob(f"{self.dataset_dir}/q*.json") + if len(files) == 0: next_qnumber = 1 else: - next_qnumber = np.max([int(f.split('/')[-1].split('.')[0][1:]) for f in files])+1 - fname = f'{self.dataset_dir}/q{next_qnumber:04d}.json' - - logger.info(f'saving record in new file {fname}') - with open(fname, 'w', encoding='utf-8') as f: + next_qnumber = ( + np.max( + [int(f.split("/")[-1].split(".")[0][1:]) for f in files] + ) + + 1 + ) + fname = f"{self.dataset_dir}/q{next_qnumber:04d}.json" + + logger.info(f"saving record in new file {fname}") + with open(fname, "w", encoding="utf-8") as f: json.dump(self.record, f, ensure_ascii=False, indent=4) class GeoQuestion: - - - def __init__(self, - question_record, - gee_dataset_list=None, - number_of_fix_iterations = 5, - ): - + def __init__( + self, + question_record, + gee_dataset_list=None, + number_of_fix_iterations=5, + ): """ constructor - + :param question_record: a QA object :param genai: the genai object to generate assets :param gee_dataset_list: list of available GEE datasets to include in the prompts. If None, will not include that information in the prompts. @@ -167,32 +180,38 @@ def __init__(self, self.question_record = question_record self.qr = self.question_record self.genai_client = init_genai_client() - self.remarks_for_prompts = '' + self.remarks_for_prompts = "" self.gee_dataset_list = gee_dataset_list self.number_of_fix_iterations = number_of_fix_iterations self.fix_code = number_of_fix_iterations > 0 if self.fix_code: - logger.info(f'will attempt to fix any code generated in max {self.number_of_fix_iterations} iterations') - self.gee_runtime = GEEPythonExecution(genai_client=self.genai_client) + logger.info( + f"will attempt to fix any code generated in max {self.number_of_fix_iterations} iterations" + ) + self.gee_runtime = GEEPythonExecution( + genai_client=self.genai_client + ) def set_remarks_for_prompts(self, remarks): self.remarks_for_prompts = remarks return self - def get_dataset_prompt_instructions(self): - dataset_instructions = f""" + dataset_instructions = ( + f""" - you must use one or more of the Google Earth Engine datasets included in the following list {self.gee_dataset_list} - you do not need to use all the datasets in the list, but you can only use the ones in that list - """ if self.gee_dataset_list is not None else '' + """ + if self.gee_dataset_list is not None + else "" + ) return dataset_instructions def get_prompt_for_python_from_question(self): - dataset_instructions = self.get_dataset_prompt_instructions() p = f""" @@ -243,11 +262,9 @@ def get_prompt_for_python_from_question(self): {self.remarks_for_prompts} """ - return remove_leading_spaces(p) - + return remove_leading_spaces(p) def get_prompt_for_abstract_graph_from_question(self): - dataset_instructions = self.get_dataset_prompt_instructions() p = f""" @@ -287,11 +304,9 @@ def get_prompt_for_abstract_graph_from_question(self): {self.remarks_for_prompts} """ - return remove_leading_spaces(p) + return remove_leading_spaces(p) def get_prompt_for_python_from_abstract_graph(self): - - dataset_instructions = self.get_dataset_prompt_instructions() p = f""" @@ -350,14 +365,11 @@ def get_prompt_for_python_from_abstract_graph(self): {self.qr['abstract_graph']} """ - return remove_leading_spaces(p) - + return remove_leading_spaces(p) def get_prompt_for_python_from_reasoning_steps(self): - dataset_instructions = self.get_dataset_prompt_instructions() - p = f""" You are an expert earth observation scientist and Python programmer. You are given a set of reasoning steps that are suposed to help answer specific earth @@ -416,33 +428,34 @@ def get_prompt_for_python_from_reasoning_steps(self): {self.qr['reasoning_steps']} """ - return remove_leading_spaces(p) - + return remove_leading_spaces(p) def run_fix_code(self, python_code): - r = self.gee_runtime.run_fix_code(python_code, - number_of_iterations=self.number_of_fix_iterations) + r = self.gee_runtime.run_fix_code( + python_code, number_of_iterations=self.number_of_fix_iterations + ) z = {} - - if len(r)==0: - z['python_code_status'] = 'error' - z['python_code_error'] = 'no running iterations' - elif 'result' in r[-1].keys(): - z['python_code_status'] = 'success' - z['python_code'] = r[-1]['code_original'] - z['python_code_result'] = r[-1]['result'] - elif 'code_original_error' in r[-1].keys(): - z['python_code_status'] = 'error' - z['python_code'] = r[-1]['code_original'] - z['python_code_error'] = r[-1]['code_original_error'] - else: - z['python_code_status'] = 'error' - z['python_code_error'] = 'internal error fixing code' - z['python_code_fix_history'] = [{k:v for k,v in ri.items() if k!='map'} for ri in r] + if len(r) == 0: + z["python_code_status"] = "error" + z["python_code_error"] = "no running iterations" + elif "result" in r[-1].keys(): + z["python_code_status"] = "success" + z["python_code"] = r[-1]["code_original"] + z["python_code_result"] = r[-1]["result"] + elif "code_original_error" in r[-1].keys(): + z["python_code_status"] = "error" + z["python_code"] = r[-1]["code_original"] + z["python_code_error"] = r[-1]["code_original_error"] + else: + z["python_code_status"] = "error" + z["python_code_error"] = "internal error fixing code" - return z + z["python_code_fix_history"] = [ + {k: v for k, v in ri.items() if k != "map"} for ri in r + ] + return z def _generate_python(self, prompt): """ @@ -459,197 +472,224 @@ def _generate_python(self, prompt): # check we can extract the tag content try: - _ = extract_xml_tag(r['answer'], 'PYTHON') - logger.debug(' found in response') + _ = extract_xml_tag(r["answer"], "PYTHON") + logger.debug(" found in response") return r - except NoTagFoundError as e: + except NoTagFoundError: # in case python is with ```python mark up - _ = extract_tag(r['answer'], 'python') - r['answer'] = r['answer'].replace('```python', '')\ - .replace('```', '') + _ = extract_tag(r["answer"], "python") + r["answer"] = ( + r["answer"] + .replace("```python", "") + .replace("```", "") + ) return r - + except NoTagFoundError as e: - if i==2: - logger.debug(f'no PYTHON tag found in genai response, response content is\n\n{r["answer"]}') + if i == 2: + logger.debug( + f'no PYTHON tag found in genai response, response content is\n\n{r["answer"]}' + ) raise e else: - logger.debug('no PYTHON tag found in genai response, trying again...') + logger.debug( + "no PYTHON tag found in genai response, trying again..." + ) def generate_python_from_question(self): - p = self.get_prompt_for_python_from_question() - - logger.info(f'calling genai to generate gee python code from question') + + logger.info(f"calling genai to generate gee python code from question") r = self._generate_python(p) self.genai_response = r - c = extract_xml_tag(r['answer'], 'PYTHON') - e = r['answer'].replace(f'{c}', '') - - if not 'question_derived' in self.qr.keys(): - self.qr['question_derived'] = {} - - self.qr['question_derived'].update( { - 'python_code': c, - 'python_code_thinking': r['thought'], - 'python_code_explanation': e, - 'python_code_remarks': self.remarks_for_prompts, - 'python_code_status': 'not_run' - }) + c = extract_xml_tag(r["answer"], "PYTHON") + e = r["answer"].replace(f"{c}", "") + + if not "question_derived" in self.qr.keys(): + self.qr["question_derived"] = {} + + self.qr["question_derived"].update( + { + "python_code": c, + "python_code_thinking": r["thought"], + "python_code_explanation": e, + "python_code_remarks": self.remarks_for_prompts, + "python_code_status": "not_run", + } + ) self.qr.save() if self.fix_code: z = self.run_fix_code(c) - self.qr['question_derived'].update(z) + self.qr["question_derived"].update(z) self.qr.save() return self.qr - - def generate_abstract_graph_from_question(self): - if 'abstract_graph' in self.qr.keys(): - raise ValueError('abstract graph already present in question record') + def generate_abstract_graph_from_question(self): + if "abstract_graph" in self.qr.keys(): + raise ValueError( + "abstract graph already present in question record" + ) p = self.get_prompt_for_abstract_graph_from_question() - logger.info(f'calling genai to generate abstract graph from question') + logger.info(f"calling genai to generate abstract graph from question") r = self.genai_client.call(p) self.genai_response = r - if not 'question_derived' in self.qr.keys(): - self.qr['question_derived'] = {} + if not "question_derived" in self.qr.keys(): + self.qr["question_derived"] = {} + self.qr["question_derived"].update( + { + "abstract_graph": extract_xml_tag(r["answer"], "GRAPH"), + "abstract_graph_thinking": r["thought"], + "abstract_graph_explanation": extract_xml_tag( + r["answer"], "EXPLANATION" + ), + "abstract_graph_remarks": self.remarks_for_prompts, + } + ) - self.qr['question_derived'].update ({ - 'abstract_graph': extract_xml_tag(r['answer'], 'GRAPH'), - 'abstract_graph_thinking': r['thought'], - 'abstract_graph_explanation': extract_xml_tag(r['answer'], 'EXPLANATION'), - 'abstract_graph_remarks': self.remarks_for_prompts - }) - - self.qr['abstract_graph'] = self.qr['question_derived']['abstract_graph'] + self.qr["abstract_graph"] = self.qr["question_derived"][ + "abstract_graph" + ] self.qr.save() return self.qr - def generate_python_from_abstract_graph(self): - p = self.get_prompt_for_python_from_abstract_graph() - logger.info(f'calling genai to generate gee python from graph') + logger.info(f"calling genai to generate gee python from graph") r = self._generate_python(p) self.genai_response = r - c = extract_xml_tag(r['answer'], 'PYTHON') - e = r['answer'].replace(f'{c}', '') - - if not 'abstract_graph_derived' in self.qr.keys(): - self.qr['abstract_graph_derived'] = {} - - self.qr['abstract_graph_derived'] = { - 'python_code': c, - 'ptyhon_code_thinking': r['thought'], - 'python_code_explanation': e, - 'python_code_remarks': self.remarks_for_prompts, - 'python_code_status': 'not_run' + c = extract_xml_tag(r["answer"], "PYTHON") + e = r["answer"].replace(f"{c}", "") + + if not "abstract_graph_derived" in self.qr.keys(): + self.qr["abstract_graph_derived"] = {} + + self.qr["abstract_graph_derived"] = { + "python_code": c, + "python_code_thinking": r["thought"], + "python_code_explanation": e, + "python_code_remarks": self.remarks_for_prompts, + "python_code_status": "not_run", } self.qr.save() if self.fix_code: z = self.run_fix_code(c) - self.qr['abstract_graph_derived'].update(z) + self.qr["abstract_graph_derived"].update(z) self.qr.save() return self.qr - def generate_python_from_reasoning_steps(self): - p = self.get_prompt_for_python_from_reasoning_steps() - logger.info(f'calling genai to generate gee python from reasoning steps') + logger.info( + f"calling genai to generate gee python from reasoning steps" + ) r = self._generate_python(p) self.genai_response = r - c = extract_xml_tag(r['answer'], 'PYTHON') - e = r['answer'].replace(f'{c}', '') - - if not 'reasoning_steps_derived' in self.qr.keys(): - self.qr['reasoning_steps_derived'] = {} - - self.qr['reasoning_steps_derived'] = { - 'python_code': c, - 'ptyhon_code_thinking': r['thought'], - 'python_code_explanation': e, - 'python_code_remarks': self.remarks_for_prompts, - 'python_code_status': 'not_run' + c = extract_xml_tag(r["answer"], "PYTHON") + e = r["answer"].replace(f"{c}", "") + + if not "reasoning_steps_derived" in self.qr.keys(): + self.qr["reasoning_steps_derived"] = {} + + self.qr["reasoning_steps_derived"] = { + "python_code": c, + "python_code_thinking": r["thought"], + "python_code_explanation": e, + "python_code_remarks": self.remarks_for_prompts, + "python_code_status": "not_run", } self.qr.save() if self.fix_code: z = self.run_fix_code(c) - self.qr['reasoning_steps_derived'].update(z) + self.qr["reasoning_steps_derived"].update(z) self.qr.save() return self.qr + # functions for direct calling with strings -def _generate_python_from_question(question: str, gee_datasets: list = None, fix_code: bool = True) -> dict: - q = QuestionRecord(question=question) - g = GeoQuestion(q, - gee_dataset_list=gee_datasets, - number_of_fix_iterations=5 if fix_code else 0) - +def _generate_python_from_question( + question: str, gee_datasets: list = None, fix_code: bool = True +) -> dict: + q = QuestionRecord(question=question) + g = GeoQuestion( + q, + gee_dataset_list=gee_datasets, + number_of_fix_iterations=5 if fix_code else 0, + ) + g.generate_python_from_question() - - return q.record['question_derived'] -def _generate_abstract_graph_from_question(question: str, gee_datasets: list = None) -> dict: + return q.record["question_derived"] + + +def _generate_abstract_graph_from_question( + question: str, gee_datasets: list = None +) -> dict: + q = QuestionRecord(question=question) + g = GeoQuestion( + q, + gee_dataset_list=gee_datasets, + ) - q = QuestionRecord(question=question) - g = GeoQuestion(q, - gee_dataset_list=gee_datasets, - ) - g.generate_abstract_graph_from_question() - - return q.record['question_derived'] - -def _generate_python_from_reasoning_steps(question: str, - reasoning_steps: str, - gee_datasets: list = None, - fix_code: bool = True) -> dict: - - q = QuestionRecord(question=question) - q['reasoning_steps'] = reasoning_steps - g = GeoQuestion(q, - gee_dataset_list=gee_datasets, - number_of_fix_iterations=5 if fix_code else 0) - + + return q.record["question_derived"] + + +def _generate_python_from_reasoning_steps( + question: str, + reasoning_steps: str, + gee_datasets: list = None, + fix_code: bool = True, +) -> dict: + q = QuestionRecord(question=question) + q["reasoning_steps"] = reasoning_steps + g = GeoQuestion( + q, + gee_dataset_list=gee_datasets, + number_of_fix_iterations=5 if fix_code else 0, + ) + g.generate_python_from_reasoning_steps() - - return q.record['reasoning_steps_derived'] - -def _generate_python_from_abstract_graph(question: str, - abstract_graph: str, - gee_datasets: list = None, - fix_code: bool = True) -> dict: - - q = QuestionRecord(question=question) - q['abstract_graph'] = abstract_graph - g = GeoQuestion(q, - gee_dataset_list=gee_datasets, - number_of_fix_iterations=5 if fix_code else 0) - + + return q.record["reasoning_steps_derived"] + + +def _generate_python_from_abstract_graph( + question: str, + abstract_graph: str, + gee_datasets: list = None, + fix_code: bool = True, +) -> dict: + q = QuestionRecord(question=question) + q["abstract_graph"] = abstract_graph + g = GeoQuestion( + q, + gee_dataset_list=gee_datasets, + number_of_fix_iterations=5 if fix_code else 0, + ) + g.generate_python_from_abstract_graph() - - return q.record['abstract_graph_derived'] + return q.record["abstract_graph_derived"] diff --git a/server/coderun.py b/src/gee_mcp/server/coderun.py similarity index 67% rename from server/coderun.py rename to src/gee_mcp/server/coderun.py index 2a66f40..0ce3e7c 100644 --- a/server/coderun.py +++ b/src/gee_mcp/server/coderun.py @@ -1,65 +1,65 @@ -import ee +import json + +import ee from loguru import logger -from .helpers import extract_xml_tag, extract_tag, remove_leading_spaces + from .genai import init_genai_client -import json +from .helpers import extract_xml_tag class GEEPythonExecution: - - def __init__(self, genai_client = None, ee_project=None): + def __init__(self, genai_client=None, ee_project=None): if genai_client is None: self.genai_client = init_genai_client() else: self.genai_client = genai_client - + self.ee_project = ee_project if ee_project is not None: ee.Authenticate() ee.Initialize(project=ee_project) - logger.debug('initialized Earth Engine API') + logger.debug("initialized Earth Engine API") else: - logger.debug('no Earth Engine project provided, assuming API is already initialized') + logger.debug( + "no Earth Engine project provided, assuming API is already initialized" + ) def exec(self, code): - try: - del(gee_main) - except: - pass - - namespace = {} - exec(code, namespace) - gee_main = namespace['gee_main'] - r = gee_main() - return r + namespace: dict = {} + exec(code, namespace) # pylint: disable=exec-used + gee_main = namespace["gee_main"] + return gee_main() def fix_code_iteration(self, code, previous_errors=[]): """ - assumes ee.Authenticate and ee.Initialized have been + assumes ee.Authenticate and ee.Initialized have been called previously. Fixes GEE Python code by calling genai with the error message and the original code, - and asking for a fixed version of the code. The prompt includes specific guidelines - to ensure that the generated code is correct and can be run in the user's environment. - The method returns a dict with the original code, the fixed code, the original error - message, the fixed graph, and an explanation of the fix. + and asking for a fixed version of the code. The prompt includes specific guidelines + to ensure that the generated code is correct and can be run in the user's environment. + The method returns a dict with the original code, the fixed code, the original error + message, the fixed graph, and an explanation of the fix. """ error = "" - + try: r = self.exec(code) - return {'result': r[0], 'map': r[1], 'code_original': code} + return {"result": r[0], "map": r[1], "code_original": code} except Exception as e: error = e - logger.debug(f'error {e}') - - if len(previous_errors)>0: - logger.debug(f'previous errors: {previous_errors}') - previous_errors = f'You already tried to fix these previous errors:\n' + '\n - '.join(previous_errors) + logger.debug(f"error {e}") + + if len(previous_errors) > 0: + logger.debug(f"previous errors: {previous_errors}") + previous_errors = ( + f"You already tried to fix these previous errors:\n" + + "\n - ".join(previous_errors) + ) else: - previous_errors = '' + previous_errors = "" fix_prompt = f""" You an expert Google Earth Engine Python API programmer and I have this python @@ -125,58 +125,61 @@ def fix_code_iteration(self, code, previous_errors=[]): thrown, not just printing a message. """ - logger.info('calling genai to fix python code') + logger.info("calling genai to fix python code") rf = self.genai_client.call(fix_prompt) - - code_fixed = extract_xml_tag(rf['answer'], 'FIXED_PYTHON') - graph_fixed = extract_xml_tag(rf['answer'], 'FIXED_PYTHON_GRAPH') - explanation_fixed = extract_xml_tag(rf['answer'], 'FIX_EXPLANATION') - - return {'code_original': code, - 'code_fixed': code_fixed, - 'code_original_error': str(error), - 'graph_fixed': graph_fixed, - 'explanation_fixed': explanation_fixed } + + code_fixed = extract_xml_tag(rf["answer"], "FIXED_PYTHON") + graph_fixed = extract_xml_tag(rf["answer"], "FIXED_PYTHON_GRAPH") + explanation_fixed = extract_xml_tag( + rf["answer"], "FIX_EXPLANATION" + ) + + return { + "code_original": code, + "code_fixed": code_fixed, + "code_original_error": str(error), + "graph_fixed": graph_fixed, + "explanation_fixed": explanation_fixed, + } def run_fix_code(self, code, number_of_iterations=5): """ Runs the provided GEE Python code and if it raises an error, calls the fix_code_iteration method to try to fix it. - This process is repeated for a maximum number of iterations until the code runs without errors or the maximum + This process is repeated for a maximum number of iterations until the code runs without errors or the maximum number of iterations is reached. The method returns the history of fixes attempted, and if successful, - + :param self: Description :param code: Python code to execute and fix if errors are found :param number_of_iterations: Number of iterations to try fixing the code if errors are found. Default is 5. :return: The history of fixes attempted. If successful, that last fix in history contains the fixed code and result. :rtype: list - + """ fix_history = [] error_history = [] for i in range(number_of_iterations): - logger.info(f'running code attempt {i+1}') - rf = self.fix_code_iteration(code, previous_errors=error_history) + logger.info(f"running code attempt {i+1}") + rf = self.fix_code_iteration(code, previous_errors=error_history) fix_history.append(rf) - if 'result' in rf.keys(): - if i>0: - logger.info('code is fixed') + if "result" in rf.keys(): + if i > 0: + logger.info("code is fixed") return fix_history else: - logger.info('code is already correct, no fix needed') + logger.info("code is already correct, no fix needed") return fix_history else: - code = rf['code_fixed'] - error_history.append(rf['code_original_error']) - logger.info(f'could not fix code in {number_of_iterations} iterations') - return fix_history + code = rf["code_fixed"] + error_history.append(rf["code_original_error"]) + logger.info(f"could not fix code in {number_of_iterations} iterations") + return fix_history def _execute_gee_python(code: str): - gee = GEEPythonExecution() try: r = gee.exec(code) - return json.dumps({'result': r[0]}, indent=2, default=str) + return json.dumps({"result": r[0]}, indent=2, default=str) except Exception as e: - return json.dumps({'errors': str(e)}, indent=2, default=str) \ No newline at end of file + return json.dumps({"errors": str(e)}, indent=2, default=str) diff --git a/server/constants.py b/src/gee_mcp/server/constants.py similarity index 100% rename from server/constants.py rename to src/gee_mcp/server/constants.py diff --git a/server/genai.py b/src/gee_mcp/server/genai.py similarity index 54% rename from server/genai.py rename to src/gee_mcp/server/genai.py index 80ec4d7..bfa0d39 100644 --- a/server/genai.py +++ b/src/gee_mcp/server/genai.py @@ -1,115 +1,116 @@ -from google import genai as google_genai -from google.genai import types -from loguru import logger import hashlib import json import os -def init_genai_client(model='gemini-3.1-pro-preview'): +from google import genai as google_genai +from google.genai import types +from loguru import logger + +def init_genai_client(model="gemini-3.1-pro-preview"): api_key = os.getenv("GEMINI_API_KEY") or os.getenv("GOOGLE_API_KEY") vertexai_project = os.getenv("VERTEXAI_PROJECT", False) vertexai_location = os.getenv("VERTEXAI_LOCATION", "global") - + if api_key: genai_client = Gemini(api_key=api_key, model=model) else: - if not vertexai_project: raise ValueError( "you must specified either an api key using GEMINI_API_KEY or GOOGLE_API_KEY environment variable or a vertexai project using VERTEXAI_PROJECT environment variable" ) - genai_client = Gemini(project=vertexai_project, location=vertexai_location) + genai_client = Gemini( + project=vertexai_project, location=vertexai_location + ) return genai_client -class Gemini: - def __init__(self, - api_key=None, - project=None, - location='global', - model = 'gemini-3.1-pro-preview', - cache_dir=None): +class Gemini: + def __init__( + self, + api_key=None, + project=None, + location="global", + model="gemini-3.1-pro-preview", + cache_dir=None, + ): """ use either api_key (for Gemini Developer API), or project + location (for VertexAI API) :param cache_dir: if set, cache responses to this directory to avoid redundant API calls """ - if api_key is None and project is None: - raise ValueError('must provide either api_key or project+location for Gemini client initialization') + raise ValueError( + "must provide either api_key or project+location for Gemini client initialization" + ) if api_key is not None: - logger.debug('google genai client using developer api') + logger.debug("google genai client using developer api") self.client = google_genai.Client(vertexai=False, api_key=api_key) else: - logger.debug(f'google genai client using vertexai api project {project} location {location}') - self.client = google_genai.Client(vertexai=True, project=project, location=location) + logger.debug( + f"google genai client using vertexai api project {project} location {location}" + ) + self.client = google_genai.Client( + vertexai=True, project=project, location=location + ) self.model = model self.cache_dir = cache_dir if cache_dir: os.makedirs(cache_dir, exist_ok=True) - logger.debug(f'response caching enabled at {cache_dir}') - logger.debug(f'genai client initialized with model {self.model}') + logger.debug(f"response caching enabled at {cache_dir}") + logger.debug(f"genai client initialized with model {self.model}") def _cache_key(self, text, include_thinking): content = f"{self.model}::{include_thinking}::{text}" return hashlib.sha256(content.encode()).hexdigest()[:16] def call(self, text, include_thinking=True): - # check cache if self.cache_dir: key = self._cache_key(text, include_thinking) cache_path = os.path.join(self.cache_dir, f"{key}.json") if os.path.exists(cache_path): - logger.debug(f'cache hit: {key}') + logger.debug(f"cache hit: {key}") with open(cache_path) as f: cached = json.load(f) - return {'answer': cached['answer'], - 'thought': cached.get('thought'), - 'response': None} + return { + "answer": cached["answer"], + "thought": cached.get("thought"), + "response": None, + } if include_thinking: thinking_conf = types.GenerateContentConfig( - thinking_config=types.ThinkingConfig( - include_thoughts=True - ) - ) + thinking_config=types.ThinkingConfig(include_thoughts=True) + ) else: thinking_conf = None # Create the multimodal content parts response = self.client.models.generate_content( - model=self.model, - contents=[ - text - ], - config=thinking_conf - + model=self.model, contents=[text], config=thinking_conf ) thought = None - answer = None + answer = None for part in response.candidates[0].content.parts: - if not part.text: - continue - if part.thought: - thought = part.text - else: - answer = part.text + if not part.text: + continue + if part.thought: + thought = part.text + else: + answer = part.text # save to cache if self.cache_dir: - with open(cache_path, 'w') as f: - json.dump({'answer': answer, 'thought': thought}, f, indent=2) - logger.debug(f'cached response: {key}') + with open(cache_path, "w") as f: + json.dump({"answer": answer, "thought": thought}, f, indent=2) + logger.debug(f"cached response: {key}") - return {'answer': answer, - 'thought': thought, - 'response': response} \ No newline at end of file + return {"answer": answer, "thought": thought, "response": response} diff --git a/server/helpers.py b/src/gee_mcp/server/helpers.py similarity index 91% rename from server/helpers.py rename to src/gee_mcp/server/helpers.py index b722272..c14bd14 100644 --- a/server/helpers.py +++ b/src/gee_mcp/server/helpers.py @@ -5,12 +5,12 @@ import json import logging import os +import re +from datetime import datetime, timedelta from typing import Any, Dict, List, Optional import ee import requests -import re -from loguru import logger from .constants import ( _REDUCER_MAP, @@ -20,35 +20,38 @@ ) from .models import RegionParams -import os -from datetime import datetime, timedelta - # removes leading spaces of each line in a string -remove_leading_spaces = lambda t: '\n'.join([l.strip() for l in t.splitlines()]) +remove_leading_spaces = lambda t: "\n".join( + [l.strip() for l in t.splitlines()] +) + class NoTagFoundError(Exception): pass + def extract_xml_tag(text, tag): - p1 = text.find(f'<{tag}>') - p2 = text.find(f'') + """Extract content between ```` and ```` in text.""" + p1 = text.find(f"<{tag}>") + p2 = text.find(f"") - if p2<=p1: - raise NoTagFoundError(f'no {tag} found in genai response') + if p1 < 0 or p2 <= p1: + raise NoTagFoundError(f"no {tag} found in genai response") + + return text[p1 + len(tag) + 2 : p2] - return text[p1+len(tag)+2:p2] def extract_tag(text, tag): - # extract the graph - pattern = r'```{tag}(.*)```'.format(tag=tag) - match = re.search(pattern, text, flags=re.DOTALL) - if match: - # extract the graph definition - content = match.group(1) - return content + """Extract the first ```{tag} ... ``` markdown fence from text. + + Uses a non-greedy match so that subsequent fences in the same text + are not consumed. + """ + pattern = rf"```{tag}(.*?)```" + if match := re.search(pattern, text, flags=re.DOTALL): + return match.group(1) + raise NoTagFoundError(f"no {tag} found in genai response") - else: - raise NoTagFoundError(f'no {tag} found in genai response') def is_file_older_than_one_hour(filepath): """ @@ -62,13 +65,13 @@ def is_file_older_than_one_hour(filepath): """ # Get the file's last modification timestamp in seconds since the epoch modification_timestamp = os.path.getmtime(filepath) - + # Convert the timestamp to a datetime object modification_time = datetime.fromtimestamp(modification_timestamp) - + # Calculate the cutoff time (one hour ago from now) cutoff_time = datetime.now() - timedelta(hours=1) - + # Compare the file's modification time with the cutoff time return modification_time < cutoff_time @@ -157,7 +160,9 @@ def _build_region(params: RegionParams) -> ee.Geometry: # ------------------------------------------------------------------ -def _check_and_split_region(region: ee.Geometry, scale: int) -> List[ee.Geometry]: +def _check_and_split_region( + region: ee.Geometry, scale: int +) -> List[ee.Geometry]: """Check pixel count and recursively split if too large.""" try: proj = ee.Projection("EPSG:4326").atScale(scale) @@ -244,7 +249,9 @@ def _download_with_fallback( depth: int = 0, ) -> List[str]: """Download with recursive split / scale-backoff.""" - download_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), "download") + download_dir = os.path.join( + os.path.dirname(os.path.dirname(__file__)), "download" + ) os.makedirs(download_dir, exist_ok=True) download_region = region.bounds().getInfo()["coordinates"] @@ -270,13 +277,16 @@ def _download_with_fallback( and "must be less than or equal to" in err_msg ): logging.info( - "Tile too large at scale=%d. depth=%d. " "Attempting fallback...", + "Tile too large at scale=%d. depth=%d. " + "Attempting fallback...", scale, depth, ) if depth < 2: results: List[str] = [] - for idx, sub in enumerate(_split_region_quadrants(region), start=1): + for idx, sub in enumerate( + _split_region_quadrants(region), start=1 + ): results.extend( _download_with_fallback( selected_bands, @@ -338,7 +348,9 @@ def _build_collection( ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE", max_cloud_cover) ) elif dataset.startswith("LANDSAT") and max_cloud_cover is not None: - collection = collection.filter(ee.Filter.lt("CLOUD_COVER", max_cloud_cover)) + collection = collection.filter( + ee.Filter.lt("CLOUD_COVER", max_cloud_cover) + ) return collection @@ -376,7 +388,9 @@ def _resolve_target_image( if expression: band_info = composite.bandNames().getInfo() band_map = {b: composite.select(b) for b in band_info} - return composite.expression(expression, band_map).rename("custom_index") + return composite.expression(expression, band_map).rename( + "custom_index" + ) if bands: band_list = [b.strip() for b in bands.split(",") if b.strip()] @@ -431,7 +445,9 @@ def _build_reducer(reducers: str): combined = _REDUCER_MAP[requested[0]]() for r_name in requested[1:]: if r_name in _REDUCER_MAP: - combined = combined.combine(_REDUCER_MAP[r_name](), sharedInputs=True) + combined = combined.combine( + _REDUCER_MAP[r_name](), sharedInputs=True + ) return combined diff --git a/server/models.py b/src/gee_mcp/server/models.py similarity index 85% rename from server/models.py rename to src/gee_mcp/server/models.py index 6d6de52..295dbf2 100644 --- a/server/models.py +++ b/src/gee_mcp/server/models.py @@ -49,7 +49,9 @@ def check_coords_or_geojson(cls, data: Any) -> Any: geojson_provided = geojson is not None bbox_provided = bbox is not None - provided_options = sum([coords_provided, geojson_provided, bbox_provided]) + provided_options = sum( + [coords_provided, geojson_provided, bbox_provided] + ) if provided_options == 0: raise ValueError( @@ -80,7 +82,9 @@ class DownloadParams(RegionParams): scale: int = Field(10, description="Pixel resolution in meters") bands: Optional[str] = Field( "B4,B3,B2", - description=("Comma-separated band names to download, " "e.g., B4,B3,B2"), + description=( + "Comma-separated band names to download, " "e.g., B4,B3,B2" + ), ) dataset: str = Field( "COPERNICUS/S2_SR_HARMONIZED", @@ -115,11 +119,15 @@ class ComputeIndexParams(RegionParams): ) index_name: Optional[str] = Field( None, - description=("Well-known spectral index: " "NDVI, NDWI, EVI, NBR, NDBI, SAVI."), + description=( + "Well-known spectral index: " "NDVI, NDWI, EVI, NBR, NDBI, SAVI." + ), ) expression: Optional[str] = Field( None, - description=("Custom band math expression, " 'e.g. "(B8 - B4) / (B8 + B4)".'), + description=( + "Custom band math expression, " 'e.g. "(B8 - B4) / (B8 + B4)".' + ), ) scale: int = Field(10, description="Pixel resolution in metres.") max_cloud_cover: Optional[float] = Field( @@ -142,9 +150,9 @@ class ComputeIndexParams(RegionParams): def check_index_or_expression(cls, data: Any) -> Any: """Ensure exactly one of index_name or expression.""" # Run the parent validator first - data = super(ComputeIndexParams, ComputeIndexParams).check_coords_or_geojson( - data - ) + data = super( + ComputeIndexParams, ComputeIndexParams + ).check_coords_or_geojson(data) if not isinstance(data, dict): return data index_name = data.get("index_name") @@ -186,7 +194,9 @@ class ZonalStatsParams(RegionParams): ) index_name: Optional[str] = Field( None, - description=("Compute stats for a spectral index " "instead of raw bands."), + description=( + "Compute stats for a spectral index " "instead of raw bands." + ), ) scale: int = Field(10, description="Pixel resolution in metres.") max_cloud_cover: Optional[float] = Field( @@ -205,7 +215,9 @@ class ZonalStatsParams(RegionParams): ) download: bool = Field( False, - description=("If true, include GeoTIFF download link " "for the composite."), + description=( + "If true, include GeoTIFF download link " "for the composite." + ), ) @@ -220,7 +232,9 @@ class TemporalCompositeParams(RegionParams): ) method: str = Field( "median", - description=("Composite method: " "median, mosaic, greenest, most_recent."), + description=( + "Composite method: " "median, mosaic, greenest, most_recent." + ), ) bands: Optional[str] = Field( "B4,B3,B2", @@ -279,9 +293,15 @@ class MaskByRasterParams(RegionParams): None, description="Inclusive upper bound for the mask range.", ) - bands: Optional[str] = Field(None, description="Comma-separated bands to analyse.") - index_name: Optional[str] = Field(None, description="Spectral index to compute.") - expression: Optional[str] = Field(None, description="Custom band math expression.") + bands: Optional[str] = Field( + None, description="Comma-separated bands to analyse." + ) + index_name: Optional[str] = Field( + None, description="Spectral index to compute." + ) + expression: Optional[str] = Field( + None, description="Custom band math expression." + ) scale: int = Field(10, description="Pixel resolution in metres.") max_cloud_cover: Optional[float] = Field( 20.0, description="Maximum cloud cover percentage (0-100)." @@ -306,9 +326,9 @@ class MaskByRasterParams(RegionParams): @classmethod def check_mask_range(cls, data: Any) -> Any: """Ensure at least one of mask_min/mask_max is provided.""" - data = super(MaskByRasterParams, MaskByRasterParams).check_coords_or_geojson( - data - ) + data = super( + MaskByRasterParams, MaskByRasterParams + ).check_coords_or_geojson(data) if not isinstance(data, dict): return data if data.get("mask_min") is None and data.get("mask_max") is None: @@ -328,8 +348,12 @@ class ThresholdAreaParams(RegionParams): description="ImageCollection ID.", ) band: Optional[str] = Field(None, description="Single band name.") - index_name: Optional[str] = Field(None, description="Spectral index to compute.") - expression: Optional[str] = Field(None, description="Custom band math expression.") + index_name: Optional[str] = Field( + None, description="Spectral index to compute." + ) + expression: Optional[str] = Field( + None, description="Custom band math expression." + ) threshold: float = Field(..., description="Threshold value.") operator: str = Field( "gte", @@ -338,9 +362,15 @@ class ThresholdAreaParams(RegionParams): mask_dataset: Optional[str] = Field( None, description="Optional ancillary mask dataset." ) - mask_band: Optional[str] = Field(None, description="Band for ancillary mask.") - mask_min: Optional[float] = Field(None, description="Ancillary mask lower bound.") - mask_max: Optional[float] = Field(None, description="Ancillary mask upper bound.") + mask_band: Optional[str] = Field( + None, description="Band for ancillary mask." + ) + mask_min: Optional[float] = Field( + None, description="Ancillary mask lower bound." + ) + mask_max: Optional[float] = Field( + None, description="Ancillary mask upper bound." + ) scale: int = Field(10, description="Pixel resolution in metres.") max_cloud_cover: Optional[float] = Field( 20.0, description="Maximum cloud cover percentage (0-100)." @@ -370,9 +400,9 @@ class ThresholdAreaParams(RegionParams): @classmethod def check_target_and_operator(cls, data: Any) -> Any: """Validate exactly one target and a valid operator.""" - data = super(ThresholdAreaParams, ThresholdAreaParams).check_coords_or_geojson( - data - ) + data = super( + ThresholdAreaParams, ThresholdAreaParams + ).check_coords_or_geojson(data) if not isinstance(data, dict): return data @@ -382,7 +412,8 @@ def check_target_and_operator(cls, data: Any) -> Any: provided = sum([has_band, has_index, has_expr]) if provided != 1: raise ValueError( - "Exactly one of band, index_name, or expression " "must be provided." + "Exactly one of band, index_name, or expression " + "must be provided." ) op = data.get("operator", "gte") @@ -415,15 +446,23 @@ class MultiPeriodParams(RegionParams): ) analysis: str = Field( "zonal_stats", - description=("Analysis type: " "zonal_stats, threshold_area, index_stats."), + description=( + "Analysis type: " "zonal_stats, threshold_area, index_stats." + ), ) band: Optional[str] = Field( None, description=("Single band name (threshold_area analysis)."), ) - bands: Optional[str] = Field(None, description="Bands for zonal_stats analysis.") - index_name: Optional[str] = Field(None, description="Spectral index to compute.") - expression: Optional[str] = Field(None, description="Custom band math expression.") + bands: Optional[str] = Field( + None, description="Bands for zonal_stats analysis." + ) + index_name: Optional[str] = Field( + None, description="Spectral index to compute." + ) + expression: Optional[str] = Field( + None, description="Custom band math expression." + ) threshold: Optional[float] = Field( None, description="Required if analysis=threshold_area.", @@ -439,9 +478,15 @@ class MultiPeriodParams(RegionParams): mask_dataset: Optional[str] = Field( None, description="Optional ancillary mask dataset." ) - mask_band: Optional[str] = Field(None, description="Band for ancillary mask.") - mask_min: Optional[float] = Field(None, description="Ancillary mask lower bound.") - mask_max: Optional[float] = Field(None, description="Ancillary mask upper bound.") + mask_band: Optional[str] = Field( + None, description="Band for ancillary mask." + ) + mask_min: Optional[float] = Field( + None, description="Ancillary mask lower bound." + ) + mask_max: Optional[float] = Field( + None, description="Ancillary mask upper bound." + ) scale: int = Field(10, description="Pixel resolution in metres.") max_cloud_cover: Optional[float] = Field( 20.0, description="Maximum cloud cover percentage (0-100)." @@ -480,7 +525,9 @@ class MultiPeriodParams(RegionParams): @classmethod def check_periods_and_analysis(cls, data: Any) -> Any: """Validate periods count and threshold requirement.""" - data = super(MultiPeriodParams, MultiPeriodParams).check_coords_or_geojson(data) + data = super( + MultiPeriodParams, MultiPeriodParams + ).check_coords_or_geojson(data) if not isinstance(data, dict): return data diff --git a/server/tools_analysis.py b/src/gee_mcp/server/tools_analysis.py similarity index 90% rename from server/tools_analysis.py rename to src/gee_mcp/server/tools_analysis.py index 0ff542e..5795621 100644 --- a/server/tools_analysis.py +++ b/src/gee_mcp/server/tools_analysis.py @@ -14,7 +14,7 @@ import json import logging -from typing import Any, Dict, List, Optional +from typing import Any, Dict, List import ee @@ -64,7 +64,8 @@ def download_satellite_image( tiles = _check_and_split_region(region, args.scale) if len(tiles) > 1: logging.info( - "Region is too large for a single download. " "Splitting into %d tiles.", + "Region is too large for a single download. " + "Splitting into %d tiles.", len(tiles), ) @@ -99,7 +100,9 @@ def download_satellite_image( ) continue - collection = collection.sort("CLOUDY_PIXEL_PERCENTAGE").limit(args.image_count) + collection = collection.sort("CLOUDY_PIXEL_PERCENTAGE").limit( + args.image_count + ) image_list = collection.toList(args.image_count) num_images_found = image_list.size().getInfo() @@ -108,11 +111,15 @@ def download_satellite_image( image = ee.Image(image_list.get(j)) date_string = ( - ee.Date(image.get("system:time_start")).format("YYYYMMdd").getInfo() + ee.Date(image.get("system:time_start")) + .format("YYYYMMdd") + .getInfo() ) if args.bands: - band_list = [b.strip() for b in args.bands.split(",") if b.strip()] + band_list = [ + b.strip() for b in args.bands.split(",") if b.strip() + ] selected_bands = image.select(band_list) else: selected_bands = image @@ -124,7 +131,8 @@ def download_satellite_image( ) if not file_paths: logging.warning( - "No files produced for tile %d, image %d " "after fallbacks.", + "No files produced for tile %d, image %d " + "after fallbacks.", i + 1, j + 1, ) @@ -178,11 +186,15 @@ def _compute_index( # Two-band normalised difference indices if len(band_names) == 2: band_vals = list(band_names.values()) - index_image = composite.normalizedDifference(band_vals).rename(name) + index_image = composite.normalizedDifference(band_vals).rename( + name + ) else: # Multi-band indices (EVI, SAVI) band_map = {k: composite.select(v) for k, v in band_names.items()} - index_image = composite.expression(spec["formula"], band_map).rename(name) + index_image = composite.expression( + spec["formula"], band_map + ).rename(name) label = name else: # Custom expression @@ -283,7 +295,9 @@ def _zonal_statistics( image = composite.normalizedDifference(band_vals).rename(name) else: band_map = {k: composite.select(v) for k, v in band_names.items()} - image = composite.expression(spec["formula"], band_map).rename(name) + image = composite.expression(spec["formula"], band_map).rename( + name + ) elif args.bands: band_list = [b.strip() for b in args.bands.split(",") if b.strip()] image = composite.select(band_list) @@ -308,7 +322,9 @@ def _zonal_statistics( combined = reducer_map[requested[0]]() for r_name in requested[1:]: if r_name in reducer_map: - combined = combined.combine(reducer_map[r_name](), sharedInputs=True) + combined = combined.combine( + reducer_map[r_name](), sharedInputs=True + ) stats = image.reduceRegion( reducer=combined, @@ -405,7 +421,9 @@ def _add_ndvi(img): return { "method": args.method, "files": files, - "message": (f"Created {args.method} composite " f"from {count} images."), + "message": ( + f"Created {args.method} composite " f"from {count} images." + ), "image_count_in_collection": count, } @@ -639,7 +657,9 @@ def _multi_period_analysis( # order varies). select_bands = args.band or args.bands if select_bands and not args.index_name and not args.expression: - band_list = [b.strip() for b in select_bands.split(",") if b.strip()] + band_list = [ + b.strip() for b in select_bands.split(",") if b.strip() + ] collection = collection.select(band_list) if args.pixel_mask_band: @@ -652,7 +672,10 @@ def _multi_period_analysis( ) ) - if args.analysis == "threshold_area" and args.temporal_method == "daily_mean": + if ( + args.analysis == "threshold_area" + and args.temporal_method == "daily_mean" + ): # Map threshold-area over individual images, average. op_name = args.operator band_name = select_bands or "custom_index" @@ -683,7 +706,9 @@ def _compute_image_area(img): with_areas = collection.map(_compute_image_area) area_list = with_areas.aggregate_array("_daily_area") - mean_area_m2 = ee.List(area_list).reduce(ee.Reducer.mean()).getInfo() or 0.0 + mean_area_m2 = ( + ee.List(area_list).reduce(ee.Reducer.mean()).getInfo() or 0.0 + ) results.append( { "label": period.label, @@ -806,36 +831,48 @@ def multi_period_analysis( "require factual verification. The extract aspects or issues would be presented to" "an Earth Observation expert for verification to increase the trustworthiness of the" "GEE Python code and its results." - "" + "" "The response is a a list of json structures, each one describing a specific aspect" "identified and containing the following fields: 'title', 'description', 'facts', " "and 'question_for_expert'." - "" + "" ) ) def extract_factuality_issues(question: str, python_code: str) -> str: - from .analysis import _extract_factuality_issues - return _extract_factuality_issues(question=question, python_code=python_code) - - + return _extract_factuality_issues( + question=question, python_code=python_code + ) @mcp.tool( description=( - "makes an assessment of a factuality issue identified in a Google Earth Engine Python" - "that attemps to answer an Earth Observation Question." \ - "" \ - "The answer includes a textual assessment, as well as possibly suggestions to update" \ - "the Google Earth Engine Python code to improve the reliability of the answer" + "Make an assessment of a factuality issue identified in a Google " + "Earth Engine Python script that attempts to answer an Earth " + "Observation question. The answer includes a textual assessment, " + "as well as possible suggestions to update the GEE Python code " + "to improve the reliability of the answer." ) ) -def _assess_factuality_issue(question: str, python_code: str) -> str: +async def assess_factuality_issue( + question: str, + python_code: str, + issue_title: str, + issue_description: str, + issue_facts: str, + issue_question_for_expert: str, +) -> str: from .analysis import _assess_factuality_issue - r = _assess_factuality_issue(question=question, python_code=python_code) - return r + return await _assess_factuality_issue( + question=question, + python_code=python_code, + issue_title=issue_title, + issue_description=issue_description, + issue_facts=issue_facts, + issue_question_for_expert=issue_question_for_expert, + ) @mcp.tool( @@ -877,16 +914,14 @@ def _assess_factuality_issue(question: str, python_code: str) -> str: """ ) ) -def get_datasets_locations_and_periods(question: str, - gee_datasets: list[dict] = None - ) -> dict: - +def get_datasets_locations_and_periods( + question: str, gee_datasets: list[dict] = None +) -> dict: from . import analysis - return analysis._get_datasets_locations_and_periods(question=question, - gee_datasets=gee_datasets) - - + return analysis._get_datasets_locations_and_periods( + question=question, gee_datasets=gee_datasets + ) @mcp.tool( @@ -908,14 +943,17 @@ def get_datasets_locations_and_periods(question: str, """ ) ) -def sensitivity_analysis(question: str, - python_code: str, - baseline_answer: str) -> str: +def sensitivity_analysis( + question: str, python_code: str, baseline_answer: str +) -> str: from . import analysis - return analysis._sensitivity_analysis(question = question, - python_code = python_code, - baseline_answer = baseline_answer) + return analysis._sensitivity_analysis( + question=question, + python_code=python_code, + baseline_answer=baseline_answer, + ) + @mcp.tool( description=( @@ -927,11 +965,13 @@ def sensitivity_analysis(question: str, """ ) ) -def identify_sensible_variables(question: str, - python_code: str, - baseline_answer: str) -> str: +def identify_sensible_variables( + question: str, python_code: str, baseline_answer: str +) -> str: from . import analysis - return analysis._identify_sensible_variables(question = question, - python_code = python_code, - baseline_answer = baseline_answer) \ No newline at end of file + return analysis._identify_sensible_variables( + question=question, + python_code=python_code, + baseline_answer=baseline_answer, + ) diff --git a/server/tools_catalogue.py b/src/gee_mcp/server/tools_catalogue.py similarity index 95% rename from server/tools_catalogue.py rename to src/gee_mcp/server/tools_catalogue.py index 29e6c72..8430272 100644 --- a/server/tools_catalogue.py +++ b/src/gee_mcp/server/tools_catalogue.py @@ -26,9 +26,10 @@ from bs4 import BeautifulSoup from markitdown import MarkItDown +from . import helpers from .app import mcp from .constants import BASE_URL -from . import helpers + # ------------------------------------------------------------------- # Tool: list_datasets @@ -40,16 +41,26 @@ def list_datasets() -> str: Returns a JSON string containing dataset IDs, URLs, and short descriptions. Results are cached for one hour first in mem, then in file. """ - if helpers._datasets_cache and (time.time() - helpers._datasets_last_update < 3600): + if helpers._datasets_cache and ( + time.time() - helpers._datasets_last_update < 3600 + ): return helpers._datasets_cache import tempfile + temp_dir = tempfile.gettempdir() - datasets_metadata_file = os.path.join(temp_dir, 'gee-datasets-metadata.json') - if os.path.exists(datasets_metadata_file) and not helpers.is_file_older_than_one_hour(datasets_metadata_file): - with open(datasets_metadata_file, 'r') as f: + datasets_metadata_file = os.path.join( + temp_dir, "gee-datasets-metadata.json" + ) + if os.path.exists( + datasets_metadata_file + ) and not helpers.is_file_older_than_one_hour(datasets_metadata_file): + with open(datasets_metadata_file, "r") as f: r = json.load(f) - r = [{k:v if v is not None else "" for k,v in ri.items()} for ri in r] + r = [ + {k: v if v is not None else "" for k, v in ri.items()} + for ri in r + ] return json.dumps(r, indent=2) try: @@ -91,13 +102,13 @@ def list_datasets() -> str: } ) - with open(datasets_metadata_file, 'w') as f: + with open(datasets_metadata_file, "w") as f: json.dump(datasets, f, indent=2) helpers._datasets_cache = json.dumps(datasets, indent=2) helpers._datasets_last_update = time.time() return helpers._datasets_cache - + except requests.exceptions.Timeout: return "Error: Request timed out while scraping datasets." except Exception as e: @@ -149,7 +160,9 @@ def _get_dataset_info(dataset_id: str) -> str: return json.dumps({"error": str(e), "id": dataset_id}) -@mcp.tool(description=("Get detailed information about a specific GEE dataset")) +@mcp.tool( + description=("Get detailed information about a specific GEE dataset") +) def get_dataset_info(dataset_id: str) -> str: """Get detailed information about a specific GEE dataset.""" return _get_dataset_info(dataset_id) @@ -214,8 +227,8 @@ def analyze_metadata(dataset_id: str) -> str: The Gemini client is created lazily so that the server can start without a Gemini API key if this tool is not invoked. """ - from .utils import analyze_dataset_metadata from .genai import Gemini + from .utils import analyze_dataset_metadata page_content = _get_dataset_info(dataset_id) if page_content.startswith("{"): @@ -361,7 +374,9 @@ def check_imagery_availability( has_bbox = all(bbox_provided) try: - collection = ee.ImageCollection(dataset_id).filterDate(start_date, end_date) + collection = ee.ImageCollection(dataset_id).filterDate( + start_date, end_date + ) if has_bbox: bbox = ee.Geometry.Rectangle([west, south, east, north]) @@ -377,7 +392,9 @@ def check_imagery_availability( stac = helpers._fetch_stac_json(cat_id) if stac: try: - stac_interval = stac["extent"]["temporal"]["interval"][0] + stac_interval = stac["extent"]["temporal"]["interval"][ + 0 + ] except (KeyError, IndexError, TypeError): pass @@ -469,9 +486,9 @@ def check_imagery_availability( earliest_ms = date_range.get("min") latest_ms = date_range.get("max") earliest_date = ( - datetime.fromtimestamp(earliest_ms / 1000, tz=timezone.utc).strftime( - "%Y-%m-%d" - ) + datetime.fromtimestamp( + earliest_ms / 1000, tz=timezone.utc + ).strftime("%Y-%m-%d") if earliest_ms else None ) @@ -512,7 +529,9 @@ def check_imagery_availability( ) sample_dates = ( [ - datetime.fromtimestamp(ts / 1000, tz=timezone.utc).strftime("%Y-%m-%d") + datetime.fromtimestamp(ts / 1000, tz=timezone.utc).strftime( + "%Y-%m-%d" + ) for ts in sample_list ] if sample_list diff --git a/server/tools_execution.py b/src/gee_mcp/server/tools_execution.py similarity index 68% rename from server/tools_execution.py rename to src/gee_mcp/server/tools_execution.py index 81b3a5a..4a57a9a 100644 --- a/server/tools_execution.py +++ b/src/gee_mcp/server/tools_execution.py @@ -5,14 +5,10 @@ - ``answer_eo_question_with_gee`` """ -import json -import logging -from typing import Any, Dict, List, Optional - -import ee from .app import mcp + # ------------------------------------------------------------------- # Tool: answer EO question by generating GEE Python code with iterative # code fixing. @@ -23,7 +19,9 @@ "code with iterative error fixing and executing it." ) ) -def generate_python_from_question(question: str, gee_datasets: list = None, fix_code: bool = True) -> dict: +def generate_python_from_question( + question: str, gee_datasets: list = None, fix_code: bool = True +) -> dict: """ Answer an Earth Observation question by generating Google Earth Engine Python code with iterative error fixing and executing it. @@ -39,18 +37,21 @@ def generate_python_from_question(question: str, gee_datasets: list = None, fix_ from .codegen import _generate_python_from_question - return _generate_python_from_question(question=question, - gee_datasets=gee_datasets, - fix_code=fix_code) + return _generate_python_from_question( + question=question, gee_datasets=gee_datasets, fix_code=fix_code + ) + @mcp.tool( description=( - "generates a graph describing an earth observation pipeline that would solve" \ - "a question. The graph nodes contain 'verbose' information about what to do at" \ + "generates a graph describing an earth observation pipeline that would solve" + "a question. The graph nodes contain 'verbose' information about what to do at" "each step but makes no reference to python or gee code" ) ) -def generate_abstract_graph_from_question(question: str, gee_datasets: list = None) -> dict: +def generate_abstract_graph_from_question( + question: str, gee_datasets: list = None +) -> dict: """ Answer an Earth Observation question by generating Google Earth Engine Python code with iterative error fixing and executing it. @@ -62,21 +63,25 @@ def generate_abstract_graph_from_question(question: str, gee_datasets: list = No from .codegen import _generate_abstract_graph_from_question - return _generate_abstract_graph_from_question(question=question, - gee_datasets=gee_datasets) + return _generate_abstract_graph_from_question( + question=question, gee_datasets=gee_datasets + ) + @mcp.tool( description=( "Answer an Earth Observation question by generating Google Earth Engine Python" - "code with iterative error fixing and executing it. The user must provide a" \ - "string describing the reasoning steps he would take to solve the question" \ + "code with iterative error fixing and executing it. The user must provide a" + "string describing the reasoning steps he would take to solve the question" "and these will be used to guide and support the code generation." ) ) -def generate_python_from_reasoning_steps(question: str, - reasoning_steps: str, - gee_datasets: list = None, - fix_code: bool = True) -> dict: +def generate_python_from_reasoning_steps( + question: str, + reasoning_steps: str, + gee_datasets: list = None, + fix_code: bool = True, +) -> dict: """ returns a json structure with the following fields: "python_code": the generated python code @@ -88,24 +93,29 @@ def generate_python_from_reasoning_steps(question: str, """ from .codegen import _generate_python_from_reasoning_steps - return _generate_python_from_reasoning_steps(question=question, - reasoning_steps=reasoning_steps, - gee_datasets=gee_datasets, - fix_code=fix_code) + return _generate_python_from_reasoning_steps( + question=question, + reasoning_steps=reasoning_steps, + gee_datasets=gee_datasets, + fix_code=fix_code, + ) + @mcp.tool( description=( "Answer an Earth Observation question by generating Google Earth Engine Python" - "code with iterative error fixing and executing it. The user must provide a" \ - "string with a graph in Mermaid format describing the earth observation pipeline "\ - "that would solve the problem. The pipeline will be used to guide and support " \ + "code with iterative error fixing and executing it. The user must provide a" + "string with a graph in Mermaid format describing the earth observation pipeline " + "that would solve the problem. The pipeline will be used to guide and support " "the code generation." ) ) -def generate_python_from_abstract_graph(question: str, - abstract_graph: str, - gee_datasets: list = None, - fix_code: bool = True) -> dict: +def generate_python_from_abstract_graph( + question: str, + abstract_graph: str, + gee_datasets: list = None, + fix_code: bool = True, +) -> dict: """ returns a json structure with the following fields: "python_code": the generated python code @@ -118,31 +128,32 @@ def generate_python_from_abstract_graph(question: str, from .codegen import _generate_python_from_abstract_graph - return _generate_python_from_abstract_graph(question=question, - abstract_graph=abstract_graph, - gee_datasets=gee_datasets, - fix_code=fix_code) - - + return _generate_python_from_abstract_graph( + question=question, + abstract_graph=abstract_graph, + gee_datasets=gee_datasets, + fix_code=fix_code, + ) @mcp.tool( description=( "Execute a given Google Earth Engine Python script and return the result. " "This tool does not generate or fix any code, it only executes the provided code " - "and returns the result or any error messages." - "" + "and returns the result or any error messages." + "" "The result is given as a json string dictionary with ONLY ONE of two possible keys 'result' " "and 'errors'. " "If the execution was successful, the 'result' key will contain the execution " - "If the execution failed, the 'errors' key will contain the error message." + "If the execution failed, the 'errors' key will contain the error message." "" ) ) def execute_gee_python(code: str) -> str: """ - Execute a given Google Earth Engine Python script and return the result. + Execute a given Google Earth Engine Python script and return the result. """ from .coderun import _execute_gee_python + return _execute_gee_python(code) diff --git a/src/gee_mcp/server/utils.py b/src/gee_mcp/server/utils.py new file mode 100644 index 0000000..b8d5b9b --- /dev/null +++ b/src/gee_mcp/server/utils.py @@ -0,0 +1,147 @@ +"""Dataset metadata extraction utilities. + +Two functions used by the catalogue tools: + +- :func:`extract_dataset_metadata` — parses the markdown form of a GEE + dataset page into structured fields (bands table, pixel size, + availability, cadence). +- :func:`analyze_dataset_metadata` — uses Gemini to analyse a dataset + description and return structured metadata. +""" + +import re + +import pandas as pd + + +def extract_dataset_metadata(t: str): + """Extract metadata from a markdown rendering of a GEE dataset page. + + :param t: markdown content of the dataset page. + :return: a dict with ``data`` (DataFrame), ``pixel_size``, + ``availability_start_date``, ``availability_end_date``, and + ``cadence``. + """ + i = 0 + r = [] + ti = t[:] + + while True: + i = ti.find("\n#") + if i == -1: + break + name = ti[i : i + ti[i + 1 :].find("\n") + 1] + ti = ti[i + len(name) + 1 :][:] + position = t.find(ti) - len(name) + level = name.count("#") + name = name.replace("\n", "").replace("#", "").strip() + r.append( + {"section": name, "header_level": level, "position": position} + ) + + for i in range(len(r)): + a = r[i]["position"] + b = r[i + 1]["position"] if i < len(r) - 1 else -1 + r[i]["content"] = t[a:b] + + r = pd.DataFrame(r) + + pixel_size = None + if "bands" in r.section.str.lower().values: + ri = r[r.section.str.lower() == "bands"].iloc[0] + m = re.search( + r"\*\*pixel size\*\*(.*?)\*\*bands", + ri.content.lower(), + flags=re.DOTALL, + ) + if m: + pixel_size = m.group(1).strip() + + availability_start_date, availability_end_date = None, None + if "page summary" in r.section.str.lower().values: + ri = r[r.section.str.lower() == "page summary"].iloc[0] + m = re.search( + r"dataset availability(\s+):(.*?)\n\n", + ri.content.lower(), + flags=re.DOTALL, + ) + if m: + dataset_availability = " ".join(m.groups()).strip() + ( + availability_start_date, + availability_end_date, + ) = dataset_availability.split("–") + + cadence = None + if "page summary" in r.section.str.lower().values: + ri = r[r.section.str.lower() == "page summary"].iloc[0] + m = re.search( + r"\ncadence(\s+):(.*?)\n\n", ri.content.lower(), flags=re.DOTALL + ) + if m: + cadence = " ".join(m.groups()).strip() + + return { + "data": r, + "pixel_size": pixel_size, + "availability_start_date": availability_start_date, + "availability_end_date": availability_end_date, + "cadence": cadence, + } + + +def analyze_dataset_metadata(genai, t): + """Use a Gemini client to extract structured metadata from a dataset page. + + :param genai: a Gemini-style client exposing ``call(prompt)``. + :param t: raw text or markdown description of the dataset. + :return: the model response (typically a dict with ``answer``). + """ + prompt = f""" + + You are an expert extractor of information from earth observation metadata. + This is the description of an earth observation dataset in Google Earth Engine. + + + {t} + + + Your tasks are: + - the dataset id + - compile a detailed description of the dataset + - extract the availability start date and end date of the dataset + - extract the pixel size of the different bands of the dataset + - extract the cadence or time resolution of the dataset + - extract a list of bands with all the data associated + - infer a list of possible applications for this dataset. + + Take into consideration the following aspects: + + - some datasets have a single, global pixel size, whilst others have different pixel + sizes for different bands. In either case extract a list of all pixel sizes + present in the dataset. + + - bands usually come described in a table with different fields like band name, + pixel size, description, value ranges, etc. Extract them all. + + - sometimes cadence might not be explicitly stated in the dataset. If this is the case + try to infer it from the full description. + + Provide your answer as a json structure such as this one: + + + {{ + "dataset_id": "COPERNICUS_S1_GRD", + "description": "this dataset contains ....", + "applications": "this dataset could be used to ....", + "availability_start": "2020-01-01T00:00:00Z", + "availability_end": "2026-01-31T06:00:00Z", + "pixel_size": [ "10 meters", "60 meters" ], + "cadence": "6 hours", + "bands": [ {{"name": "B1", "description": "coastal aerosol", "pixel_size": "10 meters", "wavelength": " 0.43 - 0.45 μm"}}, + {{"name": "B2", "description": "green", "pixel_size": "60 meters", "wavelength": " 0.46 - 0.50 μm"}} + ] + }} + + """ + return genai.call(prompt) diff --git a/tests/conftest.py b/tests/conftest.py new file mode 100644 index 0000000..7bd1b72 --- /dev/null +++ b/tests/conftest.py @@ -0,0 +1,10 @@ +"""Top-level pytest fixtures for gee_mcp. + +Sets ``GEE_SKIP_AUTH=1`` before any gee_mcp module is imported, so +``setup_gee`` is a no-op during tests (otherwise the import-time auth +chain would attempt interactive login on CI). +""" + +import os + +os.environ.setdefault("GEE_SKIP_AUTH", "1") diff --git a/tests/test_server/__init__.py b/tests/test_server/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/test_server/conftest.py b/tests/test_server/conftest.py new file mode 100644 index 0000000..a878cb1 --- /dev/null +++ b/tests/test_server/conftest.py @@ -0,0 +1,29 @@ +"""Pytest fixtures for the gee_mcp server test suite.""" + +import os + +# Ensure GEE auth is skipped before any gee_mcp import in subordinate +# fixtures. +os.environ.setdefault("GEE_SKIP_AUTH", "1") + +import pytest # noqa: E402 +from fastmcp.client import Client # noqa: E402 + +from gee_mcp.config import SERVER_MODULE as PKG # noqa: E402 + + +@pytest.fixture +async def main_mcp_client(): + """A FastMCP Client context manager for testing the server.""" + from gee_mcp.server import mcp # noqa: E402 + + async with Client(transport=mcp) as mcp_client: + yield mcp_client + + +@pytest.fixture() +def server_pkg(): + """Return the imported gee_mcp.server package.""" + import importlib + + return importlib.import_module(PKG) diff --git a/tests/test_server/test_app.py b/tests/test_server/test_app.py new file mode 100644 index 0000000..1fb14b6 --- /dev/null +++ b/tests/test_server/test_app.py @@ -0,0 +1,23 @@ +"""Tests the FastMCP application instance.""" + +import importlib + +from fastmcp import FastMCP + +from gee_mcp.config import SERVER_MODULE as PKG + + +class TestApp: + """Test the app.""" + + @staticmethod + def test_mcp_instance_name(): + """The mcp instance has the expected name.""" + app = importlib.import_module(f"{PKG}.app") + assert app.mcp.name == "gee-mcp" + + @staticmethod + def test_mcp_is_fastmcp_instance(): + """The mcp object is a FastMCP instance.""" + app = importlib.import_module(f"{PKG}.app") + assert isinstance(app.mcp, FastMCP) diff --git a/tests/test_server/test_helpers.py b/tests/test_server/test_helpers.py new file mode 100644 index 0000000..7b209bb --- /dev/null +++ b/tests/test_server/test_helpers.py @@ -0,0 +1,71 @@ +"""Tests for ``helpers`` utilities (no live GEE / Gemini).""" + +import importlib + +import pytest + +from gee_mcp.config import SERVER_MODULE as PKG + + +@pytest.fixture() +def helpers_mod(): + """Return the imported helpers module.""" + return importlib.import_module(f"{PKG}.helpers") + + +class TestExtractXmlTag: + """Test ``helpers.extract_xml_tag``.""" + + @staticmethod + def test_extracts_simple_content(helpers_mod): + """Returns content between matching tags.""" + text = "prefix hello suffix" + assert helpers_mod.extract_xml_tag(text, "FOO") == "hello" + + @staticmethod + def test_raises_on_missing_tag(helpers_mod): + """Raises ``NoTagFoundError`` when tag absent.""" + with pytest.raises(helpers_mod.NoTagFoundError): + helpers_mod.extract_xml_tag("no tags here", "FOO") + + @staticmethod + def test_raises_on_only_open(helpers_mod): + """Raises when opening tag has no closing partner.""" + with pytest.raises(helpers_mod.NoTagFoundError): + helpers_mod.extract_xml_tag("no closer", "FOO") + + +class TestExtractTag: + """Test ``helpers.extract_tag`` (markdown fenced blocks).""" + + @staticmethod + def test_extracts_fenced_block(helpers_mod): + """Returns content of the first fenced block.""" + text = "intro\n```json\n[1, 2]\n```\nouter" + out = helpers_mod.extract_tag(text, "json") + assert "[1, 2]" in out + + @staticmethod + def test_non_greedy_with_multiple_fences(helpers_mod): + """Does not consume across subsequent fences.""" + text = "```json\nfirst\n```\nmiddle\n```json\nsecond\n```" + out = helpers_mod.extract_tag(text, "json") + assert "first" in out + assert "second" not in out + + @staticmethod + def test_raises_when_missing(helpers_mod): + """Raises when no fence is present.""" + with pytest.raises(helpers_mod.NoTagFoundError): + helpers_mod.extract_tag("plain text", "json") + + +class TestRemoveLeadingSpaces: + """Test ``helpers.remove_leading_spaces`` lambda.""" + + @staticmethod + def test_strips_each_line(helpers_mod): + """Each line is independently stripped of leading whitespace.""" + text = " hello\n world\n\tfoo" + out = helpers_mod.remove_leading_spaces(text) + assert out == "hello\nworld\nfoo" diff --git a/tests/test_server/test_init.py b/tests/test_server/test_init.py new file mode 100644 index 0000000..4244817 --- /dev/null +++ b/tests/test_server/test_init.py @@ -0,0 +1,58 @@ +"""Tests the package ``__init__`` module.""" + +import importlib + +import pytest +from fastmcp import FastMCP +from fastmcp.client import Client +from fastmcp.client.transports import FastMCPTransport + +from gee_mcp.config import SERVER_MODULE as PKG + +EXPECTED_TOOLS = { + "download_satellite_image", + "compute_index", + "zonal_statistics", + "temporal_composite", + "mask_by_raster", + "threshold_area", + "multi_period_analysis", + "list_datasets", + "get_dataset_info", + "get_dataset_metadata", + "check_imagery_availability", + "extract_metadata", + "analyze_metadata", + "generate_python_from_question", + "generate_python_from_reasoning_steps", + "generate_python_from_abstract_graph", + "generate_abstract_graph_from_question", + "execute_gee_python", + "extract_factuality_issues", + "assess_factuality_issue", + "get_datasets_locations_and_periods", + "identify_sensible_variables", + "sensitivity_analysis", +} + + +class TestInit: + """Verify package wiring and tool registration.""" + + @pytest.mark.asyncio + @staticmethod + async def test_all_tools_registered( + main_mcp_client: Client[FastMCPTransport], + ): + """All expected tools are registered with the FastMCP app.""" + importlib.import_module(PKG) + tools = await main_mcp_client.list_tools() + registered = {tool.name for tool in tools} + missing = EXPECTED_TOOLS - registered + assert not missing, f"Missing tools: {missing}" + + @staticmethod + def test_mcp_exported(): + """``mcp`` is re-exported from the package.""" + pkg = importlib.import_module(PKG) + assert isinstance(pkg.mcp, FastMCP) diff --git a/tests/test_server/test_main.py b/tests/test_server/test_main.py new file mode 100644 index 0000000..1492439 --- /dev/null +++ b/tests/test_server/test_main.py @@ -0,0 +1,24 @@ +"""Tests the ``__main__`` entry point.""" + +import importlib +from unittest.mock import patch + +from gee_mcp.config import SERVER_MODULE as PKG + + +class TestMain: + """Test class for main.""" + + @staticmethod + def test_main_calls_mcp_run_with_stdio(): + """``main()`` invokes ``mcp.run(transport='stdio')``.""" + main_mod = importlib.import_module(f"{PKG}.__main__") + with patch(f"{PKG}.__main__.mcp.run") as mock_run: + main_mod.main() + mock_run.assert_called_once_with(transport="stdio") + + @staticmethod + def test_main_is_callable(): + """``main`` is exported and callable.""" + main_mod = importlib.import_module(f"{PKG}.__main__") + assert callable(main_mod.main) diff --git a/tests/test_server/test_models.py b/tests/test_server/test_models.py new file mode 100644 index 0000000..ca9edd7 --- /dev/null +++ b/tests/test_server/test_models.py @@ -0,0 +1,133 @@ +"""Tests for Pydantic models in ``gee_mcp.server.models``.""" + +import importlib + +import pytest +from pydantic import ValidationError + +from gee_mcp.config import SERVER_MODULE as PKG + + +@pytest.fixture() +def models_mod(): + """Return the imported models module.""" + return importlib.import_module(f"{PKG}.models") + + +class TestRegionParams: + """Test ``RegionParams`` validation.""" + + @staticmethod + def test_accepts_lat_lon(models_mod): + """Latitude + longitude is accepted.""" + params = models_mod.RegionParams(latitude=10.0, longitude=20.0) + assert params.latitude == 10.0 + assert params.longitude == 20.0 + + @staticmethod + def test_accepts_bounding_box(models_mod): + """Four-element bounding box is accepted.""" + params = models_mod.RegionParams(bounding_box=[0, 0, 1, 1]) + assert params.bounding_box == [0, 0, 1, 1] + + @staticmethod + def test_rejects_no_location(models_mod): + """Validation fails when no location is supplied.""" + with pytest.raises(ValidationError): + models_mod.RegionParams() + + @staticmethod + def test_rejects_multiple_locations(models_mod): + """Validation fails when more than one location form is given.""" + with pytest.raises(ValidationError): + models_mod.RegionParams( + latitude=1.0, longitude=2.0, bounding_box=[0, 0, 1, 1] + ) + + @staticmethod + def test_rejects_short_bounding_box(models_mod): + """Validation fails when bounding box has wrong arity.""" + with pytest.raises(ValidationError): + models_mod.RegionParams(bounding_box=[0, 0, 1]) + + +class TestComputeIndexParams: + """Test ``ComputeIndexParams`` cross-field validation.""" + + @staticmethod + def test_requires_index_or_expression(models_mod): + """Either index_name or expression must be provided.""" + with pytest.raises(ValidationError): + models_mod.ComputeIndexParams( + latitude=10.0, + longitude=20.0, + start_date="2024-01-01", + end_date="2024-02-01", + ) + + @staticmethod + def test_rejects_both_index_and_expression(models_mod): + """Cannot supply both index_name and expression.""" + with pytest.raises(ValidationError): + models_mod.ComputeIndexParams( + latitude=10.0, + longitude=20.0, + start_date="2024-01-01", + end_date="2024-02-01", + index_name="NDVI", + expression="(B8 - B4) / (B8 + B4)", + ) + + @staticmethod + def test_unknown_index_rejected(models_mod): + """Unknown index_name fails validation.""" + with pytest.raises(ValidationError): + models_mod.ComputeIndexParams( + latitude=10.0, + longitude=20.0, + start_date="2024-01-01", + end_date="2024-02-01", + index_name="NOT_REAL", + ) + + +class TestMultiPeriodParams: + """Test ``MultiPeriodParams`` cross-field validation.""" + + @staticmethod + def test_requires_two_periods(models_mod): + """Fewer than two periods is rejected.""" + with pytest.raises(ValidationError): + models_mod.MultiPeriodParams( + latitude=0.0, + longitude=0.0, + periods=[ + models_mod.DateRange( + label="a", + start_date="2024-01-01", + end_date="2024-02-01", + ) + ], + ) + + @staticmethod + def test_threshold_required_for_threshold_area(models_mod): + """threshold_area analysis requires a threshold value.""" + with pytest.raises(ValidationError): + models_mod.MultiPeriodParams( + latitude=0.0, + longitude=0.0, + analysis="threshold_area", + periods=[ + models_mod.DateRange( + label="a", + start_date="2024-01-01", + end_date="2024-02-01", + ), + models_mod.DateRange( + label="b", + start_date="2024-03-01", + end_date="2024-04-01", + ), + ], + )