feat: update output attribute handling (#3329)
* refactor: improve function structure in _build_results * fix: remove function call that overrides Component.outputs * refactor: Add handling for outputs in __getattr__ method.
This commit is contained in:
Gabriel Luiz Freitas Almeida
GitHub
parent
93537933c3
commit
bb923cf9e1
4 changed files with 126 additions and 116 deletions
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@ -384,6 +384,8 @@ class Component(CustomComponent):
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return self.__dict__["_attributes"][name]
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if "_inputs" in self.__dict__ and name in self.__dict__["_inputs"]:
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return self.__dict__["_inputs"][name].value
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if "_outputs" in self.__dict__ and name in self.__dict__["_outputs"]:
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return self.__dict__["_outputs"][name]
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if name in BACKWARDS_COMPATIBLE_ATTRIBUTES:
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return self.__dict__[f"_{name}"]
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if name.startswith("_") and name[1:] in BACKWARDS_COMPATIBLE_ATTRIBUTES:
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@ -500,6 +502,7 @@ class Component(CustomComponent):
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self.outputs = [Output(**output) for output in outputs]
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for output in self.outputs:
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setattr(self, output.name, output)
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self._outputs[output.name] = output
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def get_trace_as_inputs(self):
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predefined_inputs = {
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@ -539,8 +542,6 @@ class Component(CustomComponent):
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_results = {}
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_artifacts = {}
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if hasattr(self, "outputs"):
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if self._vertex:
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self._set_outputs(self._vertex.outputs)
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for output in self.outputs:
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# Build the output if it's connected to some other vertex
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# or if it's not connected to any vertex
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@ -554,6 +555,7 @@ class Component(CustomComponent):
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method: Callable = getattr(self, output.method)
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if output.cache and output.value != UNDEFINED:
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_results[output.name] = output.value
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result = output.value
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else:
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result = method()
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# If the method is asynchronous, we need to await it
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@ -568,33 +570,33 @@ class Component(CustomComponent):
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result.set_flow_id(self._vertex.graph.flow_id)
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_results[output.name] = result
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output.value = result
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custom_repr = self.custom_repr()
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if custom_repr is None and isinstance(result, (dict, Data, str)):
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custom_repr = result
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if not isinstance(custom_repr, str):
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custom_repr = str(custom_repr)
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raw = result
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if self.status is None:
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artifact_value = raw
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else:
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artifact_value = self.status
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raw = self.status
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custom_repr = self.custom_repr()
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if custom_repr is None and isinstance(result, (dict, Data, str)):
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custom_repr = result
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if not isinstance(custom_repr, str):
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custom_repr = str(custom_repr)
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raw = result
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if self.status is None:
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artifact_value = raw
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else:
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artifact_value = self.status
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raw = self.status
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if hasattr(raw, "data") and raw is not None:
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raw = raw.data
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if raw is None:
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raw = custom_repr
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if hasattr(raw, "data") and raw is not None:
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raw = raw.data
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if raw is None:
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raw = custom_repr
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elif hasattr(raw, "model_dump") and raw is not None:
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raw = raw.model_dump()
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if raw is None and isinstance(result, (dict, Data, str)):
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raw = result.data if isinstance(result, Data) else result
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artifact_type = get_artifact_type(artifact_value, result)
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raw, artifact_type = post_process_raw(raw, artifact_type)
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artifact = {"repr": custom_repr, "raw": raw, "type": artifact_type}
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_artifacts[output.name] = artifact
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self._output_logs[output.name] = self._logs
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self._logs = []
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elif hasattr(raw, "model_dump") and raw is not None:
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raw = raw.model_dump()
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if raw is None and isinstance(result, (dict, Data, str)):
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raw = result.data if isinstance(result, Data) else result
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artifact_type = get_artifact_type(artifact_value, result)
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raw, artifact_type = post_process_raw(raw, artifact_type)
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artifact = {"repr": custom_repr, "raw": raw, "type": artifact_type}
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_artifacts[output.name] = artifact
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self._output_logs[output.name] = self._logs
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self._logs = []
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self._artifacts = _artifacts
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self._results = _results
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if self._tracing_service:
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55
src/backend/base/poetry.lock
generated
55
src/backend/base/poetry.lock
generated
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@ -365,17 +365,17 @@ files = [
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[[package]]
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name = "boto3"
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version = "1.34.159"
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version = "1.34.161"
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description = "The AWS SDK for Python"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "boto3-1.34.159-py3-none-any.whl", hash = "sha256:21120d23cc37c0e80dc4f64434bc5664d2a5645dcd9bf8a8fa97ed5c82164ca0"},
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{file = "boto3-1.34.159.tar.gz", hash = "sha256:ffe7bbb88ba81b5d54bc8fa0cfb2f3b7fe63a6cffa0f9207df2ef5c22a1c0587"},
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{file = "boto3-1.34.161-py3-none-any.whl", hash = "sha256:4ef285334a0edc3047e27a04caf00f7742e32c0f03a361101e768014ac5709dd"},
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{file = "boto3-1.34.161.tar.gz", hash = "sha256:a872d8fdb3203c1eb0b12fa9e9d879e6f7fd02983a485f02189e6d5914ccd834"},
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]
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[package.dependencies]
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botocore = ">=1.34.159,<1.35.0"
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botocore = ">=1.34.161,<1.35.0"
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jmespath = ">=0.7.1,<2.0.0"
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s3transfer = ">=0.10.0,<0.11.0"
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@ -384,13 +384,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
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[[package]]
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name = "botocore"
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version = "1.34.159"
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version = "1.34.161"
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description = "Low-level, data-driven core of boto 3."
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "botocore-1.34.159-py3-none-any.whl", hash = "sha256:7633062491457419a49f5860c014251ae85689f78266a3ce020c2c8688a76b97"},
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{file = "botocore-1.34.159.tar.gz", hash = "sha256:dc28806eb21e3c8d690c422530dff8b4b242ac033cbe98f160a9d37796c09cb1"},
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{file = "botocore-1.34.161-py3-none-any.whl", hash = "sha256:6c606d2da6f62fde06880aff1190566af208875c29938b6b68741e607817975a"},
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{file = "botocore-1.34.161.tar.gz", hash = "sha256:16381bfb786142099abf170ce734b95a402a3a7f8e4016358712ac333c5568b2"},
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]
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[package.dependencies]
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@ -1983,13 +1983,13 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
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[[package]]
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name = "google-cloud-aiplatform"
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version = "1.61.0"
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version = "1.62.0"
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description = "Vertex AI API client library"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "google-cloud-aiplatform-1.61.0.tar.gz", hash = "sha256:648e3cd7bb75be706d3c31d852a3d4d8a2e616ad4db4cf520ef4430615cf8ad9"},
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{file = "google_cloud_aiplatform-1.61.0-py2.py3-none-any.whl", hash = "sha256:57b36d5fa085e68197e9fc576c43263a7cad320483aa3b166bcd1fdc7e8f49e7"},
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{file = "google-cloud-aiplatform-1.62.0.tar.gz", hash = "sha256:e15d5b2a99e30d4a16f4c51cfb8129962e6da41a9027d2ea696abe0e2f006fe8"},
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{file = "google_cloud_aiplatform-1.62.0-py2.py3-none-any.whl", hash = "sha256:d7738e0fd4494a54ae08a51755a2143d58937cba2db826189771f45566c9ee3c"},
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]
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[package.dependencies]
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@ -2011,8 +2011,8 @@ cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow
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datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)"]
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endpoint = ["requests (>=2.28.1)"]
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full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "tqdm (>=4.23.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)"]
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langchain = ["langchain (>=0.1.16,<0.3)", "langchain-core (<0.3)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "tenacity (<=8.3)"]
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langchain-testing = ["absl-py", "cloudpickle (>=3.0,<4.0)", "google-cloud-trace (<2)", "langchain (>=0.1.16,<0.3)", "langchain-core (<0.3)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "pydantic (>=2.6.3,<3)", "pytest-xdist", "tenacity (<=8.3)"]
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langchain = ["langchain (>=0.1.16,<0.3)", "langchain-core (<0.3)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "orjson (<=3.10.6)", "tenacity (<=8.3)"]
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langchain-testing = ["absl-py", "cloudpickle (>=3.0,<4.0)", "google-cloud-trace (<2)", "langchain (>=0.1.16,<0.3)", "langchain-core (<0.3)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "orjson (<=3.10.6)", "pydantic (>=2.6.3,<3)", "pytest-xdist", "tenacity (<=8.3)"]
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lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"]
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metadata = ["numpy (>=1.15.0)", "pandas (>=1.0.0)"]
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pipelines = ["pyyaml (>=5.3.1,<7)"]
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@ -2770,18 +2770,18 @@ testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)",
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[[package]]
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name = "importlib-resources"
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version = "6.4.0"
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version = "6.4.2"
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description = "Read resources from Python packages"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "importlib_resources-6.4.0-py3-none-any.whl", hash = "sha256:50d10f043df931902d4194ea07ec57960f66a80449ff867bfe782b4c486ba78c"},
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{file = "importlib_resources-6.4.0.tar.gz", hash = "sha256:cdb2b453b8046ca4e3798eb1d84f3cce1446a0e8e7b5ef4efb600f19fc398145"},
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{file = "importlib_resources-6.4.2-py3-none-any.whl", hash = "sha256:8bba8c54a8a3afaa1419910845fa26ebd706dc716dd208d9b158b4b6966f5c5c"},
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{file = "importlib_resources-6.4.2.tar.gz", hash = "sha256:6cbfbefc449cc6e2095dd184691b7a12a04f40bc75dd4c55d31c34f174cdf57a"},
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]
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[package.extras]
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docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
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testing = ["jaraco.test (>=5.4)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)", "zipp (>=3.17)"]
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doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
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test = ["jaraco.test (>=5.4)", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)", "zipp (>=3.17)"]
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[[package]]
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name = "iniconfig"
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@ -6088,13 +6088,13 @@ files = [
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[[package]]
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name = "sentry-sdk"
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version = "2.12.0"
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version = "2.13.0"
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description = "Python client for Sentry (https://sentry.io)"
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optional = false
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python-versions = ">=3.6"
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files = [
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{file = "sentry_sdk-2.12.0-py2.py3-none-any.whl", hash = "sha256:7a8d5163d2ba5c5f4464628c6b68f85e86972f7c636acc78aed45c61b98b7a5e"},
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{file = "sentry_sdk-2.12.0.tar.gz", hash = "sha256:8763840497b817d44c49b3fe3f5f7388d083f2337ffedf008b2cdb63b5c86dc6"},
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{file = "sentry_sdk-2.13.0-py2.py3-none-any.whl", hash = "sha256:6beede8fc2ab4043da7f69d95534e320944690680dd9a963178a49de71d726c6"},
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{file = "sentry_sdk-2.13.0.tar.gz", hash = "sha256:8d4a576f7a98eb2fdb40e13106e41f330e5c79d72a68be1316e7852cf4995260"},
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]
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[package.dependencies]
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@ -6123,6 +6123,7 @@ httpx = ["httpx (>=0.16.0)"]
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huey = ["huey (>=2)"]
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huggingface-hub = ["huggingface-hub (>=0.22)"]
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langchain = ["langchain (>=0.0.210)"]
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litestar = ["litestar (>=2.0.0)"]
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loguru = ["loguru (>=0.5)"]
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openai = ["openai (>=1.0.0)", "tiktoken (>=0.3.0)"]
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opentelemetry = ["opentelemetry-distro (>=0.35b0)"]
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@ -6140,18 +6141,18 @@ tornado = ["tornado (>=6)"]
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[[package]]
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name = "setuptools"
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version = "72.1.0"
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version = "72.2.0"
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description = "Easily download, build, install, upgrade, and uninstall Python packages"
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "setuptools-72.1.0-py3-none-any.whl", hash = "sha256:5a03e1860cf56bb6ef48ce186b0e557fdba433237481a9a625176c2831be15d1"},
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{file = "setuptools-72.1.0.tar.gz", hash = "sha256:8d243eff56d095e5817f796ede6ae32941278f542e0f941867cc05ae52b162ec"},
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{file = "setuptools-72.2.0-py3-none-any.whl", hash = "sha256:f11dd94b7bae3a156a95ec151f24e4637fb4fa19c878e4d191bfb8b2d82728c4"},
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{file = "setuptools-72.2.0.tar.gz", hash = "sha256:80aacbf633704e9c8bfa1d99fa5dd4dc59573efcf9e4042c13d3bcef91ac2ef9"},
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]
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[package.extras]
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core = ["importlib-metadata (>=6)", "importlib-resources (>=5.10.2)", "jaraco.text (>=3.7)", "more-itertools (>=8.8)", "ordered-set (>=3.1.1)", "packaging (>=24)", "platformdirs (>=2.6.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
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doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
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doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
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test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "mypy (==1.11.*)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (<0.4)", "pytest-ruff (>=0.2.1)", "pytest-ruff (>=0.3.2)", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
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[[package]]
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@ -6241,13 +6242,13 @@ files = [
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[[package]]
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name = "soupsieve"
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version = "2.5"
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version = "2.6"
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description = "A modern CSS selector implementation for Beautiful Soup."
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optional = false
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python-versions = ">=3.8"
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files = [
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{file = "soupsieve-2.5-py3-none-any.whl", hash = "sha256:eaa337ff55a1579b6549dc679565eac1e3d000563bcb1c8ab0d0fefbc0c2cdc7"},
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{file = "soupsieve-2.5.tar.gz", hash = "sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690"},
|
||||
{file = "soupsieve-2.6-py3-none-any.whl", hash = "sha256:e72c4ff06e4fb6e4b5a9f0f55fe6e81514581fca1515028625d0f299c602ccc9"},
|
||||
{file = "soupsieve-2.6.tar.gz", hash = "sha256:e2e68417777af359ec65daac1057404a3c8a5455bb8abc36f1a9866ab1a51abb"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
|
|||
|
|
@ -27,7 +27,7 @@ def ingestion_graph():
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# Ingestion Graph
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||||
file_component = FileComponent(_id="file-123")
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file_component.set(path="test.txt")
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||||
file_component.set_output_value("data", Data(text="This is a test file."))
|
||||
file_component.set_on_output("data", value=Data(text="This is a test file."))
|
||||
text_splitter = SplitTextComponent(_id="text-splitter-123")
|
||||
text_splitter.set(data_inputs=file_component.load_file)
|
||||
openai_embeddings = OpenAIEmbeddingsComponent(_id="openai-embeddings-123")
|
||||
|
|
@ -41,10 +41,9 @@ def ingestion_graph():
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|||
api_endpoint="https://astra.example.com",
|
||||
token="token",
|
||||
)
|
||||
vector_store.set_output_value("vector_store", "mock_vector_store")
|
||||
vector_store.set_output_value("base_retriever", "mock_retriever")
|
||||
vector_store.set_output_value("search_results", [Data(text="This is a test file.")])
|
||||
|
||||
vector_store.set_on_output("vector_store", value="mock_vector_store")
|
||||
vector_store.set_on_output("base_retriever", value="mock_retriever")
|
||||
vector_store.set_on_output("search_results", value=[Data(text="This is a test file.")])
|
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ingestion_graph = Graph(file_component, vector_store)
|
||||
return ingestion_graph
|
||||
|
||||
|
|
@ -63,10 +62,15 @@ def rag_graph():
|
|||
embedding=openai_embeddings.build_embeddings,
|
||||
)
|
||||
# Mock search_documents
|
||||
rag_vector_store.get_output("search_results").value = [
|
||||
Data(data={"text": "Hello, world!"}),
|
||||
Data(data={"text": "Goodbye, world!"}),
|
||||
]
|
||||
rag_vector_store.set_on_output(
|
||||
"search_results",
|
||||
value=[
|
||||
Data(data={"text": "Hello, world!"}),
|
||||
Data(data={"text": "Goodbye, world!"}),
|
||||
],
|
||||
)
|
||||
rag_vector_store.set_on_output("base_retriever", value="mock_retriever")
|
||||
rag_vector_store.set_on_output("vector_store", value="mock_vector_store")
|
||||
parse_data = ParseDataComponent(_id="parse-data-123")
|
||||
parse_data.set(data=rag_vector_store.search_documents)
|
||||
prompt_component = PromptComponent(_id="prompt-123")
|
||||
|
|
@ -82,7 +86,7 @@ def rag_graph():
|
|||
|
||||
openai_component = OpenAIModelComponent(_id="openai-123")
|
||||
openai_component.set(api_key="sk-123", openai_api_base="https://api.openai.com/v1")
|
||||
openai_component.set_output_value("text_output", "Hello, world!")
|
||||
openai_component.set_on_output("text_output", value="Hello, world!")
|
||||
openai_component.set(input_value=prompt_component.build_prompt)
|
||||
|
||||
chat_output = ChatOutput(_id="chatoutput-123")
|
||||
|
|
@ -112,7 +116,7 @@ def test_vector_store_rag(ingestion_graph, rag_graph):
|
|||
]
|
||||
for ids, graph, len_results in zip([ingestion_ids, rag_ids], [ingestion_graph, rag_graph], [5, 8]):
|
||||
results = []
|
||||
for result in graph.start():
|
||||
for result in graph.start(config={"output": {"cache": True}}):
|
||||
results.append(result)
|
||||
|
||||
assert len(results) == len_results
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue