feat: add dataset functions

gptscript/datasets.py

@@ -0,0 +1,25 @@
+from typing import Dict
+from pydantic import BaseModel
+
+class DatasetElementMeta(BaseModel):
+    name: str
+    description: str
+
+
+class DatasetElement(BaseModel):
+    name: str
+    description: str
+    contents: str
+
+
+class DatasetMeta(BaseModel):
+    id: str
+    name: str
+    description: str
+
+
+class Dataset(BaseModel):
+    id: str
+    name: str
+    description: str
+    elements: Dict[str, DatasetElementMeta]

gptscript/gptscript.py

@@ -7,6 +7,7 @@
 
 from gptscript.confirm import AuthResponse
 from gptscript.credentials import Credential, to_credential
+from gptscript.datasets import DatasetMeta, Dataset, DatasetElementMeta, DatasetElement
 from gptscript.frame import RunFrame, CallFrame, PromptFrame, Program
 from gptscript.opts import GlobalOptions
 from gptscript.prompt import PromptResponse
@@ -210,6 +211,86 @@ async def delete_credential(self, context: str = "default", name: str = "") -> s
             {"context": [context], "name": name}
         )
 
+    async def list_datasets(self, workspace: str) -> List[DatasetMeta]:
+        if workspace == "":
+            workspace = os.environ["GPTSCRIPT_WORKSPACE_DIR"]
+
+        res = await self._run_basic_command(
+            "datasets",
+            {"input": "{}", "workspace": workspace, "datasetToolRepo": self.opts.DatasetToolRepo}
+        )
+        return [DatasetMeta.model_validate(d) for d in json.loads(res)]
+
+    async def create_dataset(self, workspace: str, name: str, description: str = "") -> Dataset:
+        if workspace == "":
+            workspace = os.environ["GPTSCRIPT_WORKSPACE_DIR"]
+
+        if name == "":
+            raise ValueError("name cannot be empty")
+
+        res = await self._run_basic_command(
+            "datasets/create",
+            {"input": json.dumps({"datasetName": name, "datasetDescription": description}),
+             "workspace": workspace,
+             "datasetToolRepo": self.opts.DatasetToolRepo}
+        )
+        return Dataset.model_validate_json(res)
+
+    async def add_dataset_element(self, workspace: str, datasetID: str, elementName: str, elementContent: str,
+                                  elementDescription: str = "") -> DatasetElementMeta:
+        if workspace == "":
+            workspace = os.environ["GPTSCRIPT_WORKSPACE_DIR"]
+
+        if datasetID == "":
+            raise ValueError("datasetID cannot be empty")
+        elif elementName == "":
+            raise ValueError("elementName cannot be empty")
+        elif elementContent == "":
+            raise ValueError("elementContent cannot be empty")
+
+        res = await self._run_basic_command(
+            "datasets/add-element",
+            {"input": json.dumps({"datasetID": datasetID,
+                                  "elementName": elementName,
+                                  "elementContent": elementContent,
+                                  "elementDescription": elementDescription}),
+             "workspace": workspace,
+             "datasetToolRepo": self.opts.DatasetToolRepo}
+        )
+        return DatasetElementMeta.model_validate_json(res)
+
+    async def list_dataset_elements(self, workspace: str, datasetID: str) -> List[DatasetElementMeta]:
+        if workspace == "":
+            workspace = os.environ["GPTSCRIPT_WORKSPACE_DIR"]
+
+        if datasetID == "":
+            raise ValueError("datasetID cannot be empty")
+
+        res = await self._run_basic_command(
+            "datasets/list-elements",
+            {"input": json.dumps({"datasetID": datasetID}),
+             "workspace": workspace,
+             "datasetToolRepo": self.opts.DatasetToolRepo}
+        )
+        return [DatasetElementMeta.model_validate(d) for d in json.loads(res)]
+
+    async def get_dataset_element(self, workspace: str, datasetID: str, elementName: str) -> DatasetElement:
+        if workspace == "":
+            workspace = os.environ["GPTSCRIPT_WORKSPACE_DIR"]
+
+        if datasetID == "":
+            raise ValueError("datasetID cannot be empty")
+        elif elementName == "":
+            raise ValueError("elementName cannot be empty")
+
+        res = await self._run_basic_command(
+            "datasets/get-element",
+            {"input": json.dumps({"datasetID": datasetID, "element": elementName}),
+             "workspace": workspace,
+             "datasetToolRepo": self.opts.DatasetToolRepo}
+        )
+        return DatasetElement.model_validate_json(res)
+
 
 def _get_command():
     if os.getenv("GPTSCRIPT_BIN") is not None:

gptscript/opts.py

@@ -12,6 +12,7 @@ def __init__(
             defaultModelProvider: str = "",
             defaultModel: str = "",
             cacheDir: str = "",
+            datasetToolRepo: str = "",
             env: list[str] = None,
     ):
         self.URL = url
@@ -21,6 +22,7 @@ def __init__(
         self.DefaultModel = defaultModel
         self.DefaultModelProvider = defaultModelProvider
         self.CacheDir = cacheDir
+        self.DatasetToolRepo = datasetToolRepo
         if env is None:
             env = [f"{k}={v}" for k, v in os.environ.items()]
         elif isinstance(env, dict):
@@ -38,6 +40,7 @@ def merge(self, other: Self) -> Self:
         cp.DefaultModel = other.DefaultModel if other.DefaultModel != "" else self.DefaultModel
         cp.DefaultModelProvider = other.DefaultModelProvider if other.DefaultModelProvider != "" else self.DefaultModelProvider
         cp.CacheDir = other.CacheDir if other.CacheDir != "" else self.CacheDir
+        cp.DatasetToolRepo = other.DatasetToolRepo if other.DatasetToolRepo != "" else self.DatasetToolRepo
         cp.Env = (other.Env or [])
         cp.Env.extend(self.Env or [])
         return cp
@@ -77,8 +80,9 @@ def __init__(self,
                  defaultModelProvider: str = "",
                  defaultModel: str = "",
                  cacheDir: str = "",
+                 datasetToolDir: str = "",
                  ):
-        super().__init__(url, token, apiKey, baseURL, defaultModelProvider, defaultModel, cacheDir, env)
+        super().__init__(url, token, apiKey, baseURL, defaultModelProvider, defaultModel, cacheDir, datasetToolDir, env)
         self.input = input
         self.disableCache = disableCache
         self.subTool = subTool

requirements.txt

@@ -10,4 +10,5 @@ setuptools==69.1.1
 twine==5.0.0
 build==1.1.1
 httpx==0.27.0
-pywin32==306; sys_platform == 'win32'
+pydantic==2.9.2
+pywin32==306; sys_platform == 'win32'

tests/test_gptscript.py

@@ -4,6 +4,7 @@
 import os
 import platform
 import subprocess
+import tempfile
 from datetime import datetime, timedelta, timezone
 from time import sleep
 
@@ -755,3 +756,39 @@ async def test_credentials(gptscript):
 
     res = await gptscript.delete_credential(name=name)
     assert not res.startswith("an error occurred"), "Unexpected error deleting credential: " + res
+
+@pytest.mark.asyncio
+async def test_datasets(gptscript):
+    with tempfile.TemporaryDirectory(prefix="py-gptscript_") as tempdir:
+        dataset_name = str(os.urandom(8).hex())
+
+        # Create dataset
+        dataset = await gptscript.create_dataset(tempdir, dataset_name, "this is a test dataset")
+        assert dataset.id != "", "Expected dataset id to be set"
+        assert dataset.name == dataset_name, "Expected dataset name to match"
+        assert dataset.description == "this is a test dataset", "Expected dataset description to match"
+        assert len(dataset.elements) == 0, "Expected dataset elements to be empty"
+
+        # Add an element
+        element_meta = await gptscript.add_dataset_element(tempdir, dataset.id, "element1", "element1 contents", "element1 description")
+        assert element_meta.name == "element1", "Expected element name to match"
+        assert element_meta.description == "element1 description", "Expected element description to match"
+
+        # Get the element
+        element = await gptscript.get_dataset_element(tempdir, dataset.id, "element1")
+        assert element.name == "element1", "Expected element name to match"
+        assert element.contents == "element1 contents", "Expected element contents to match"
+        assert element.description == "element1 description", "Expected element description to match"
+
+        # List elements in the dataset
+        elements = await gptscript.list_dataset_elements(tempdir, dataset.id)
+        assert len(elements) == 1, "Expected one element in the dataset"
+        assert elements[0].name == "element1", "Expected element name to match"
+        assert elements[0].description == "element1 description", "Expected element description to match"
+
+        # List datasets
+        datasets = await gptscript.list_datasets(tempdir)
+        assert len(datasets) > 0, "Expected at least one dataset"
+        assert datasets[0].id == dataset.id, "Expected dataset id to match"
+        assert datasets[0].name == dataset_name, "Expected dataset name to match"
+        assert datasets[0].description == "this is a test dataset", "Expected dataset description to match"

tox.ini

@@ -6,6 +6,7 @@ deps =
 	httpx
 	pytest
 	pytest-asyncio
+	pydantic
 
 passenv =
 	OPENAI_API_KEY