Revert some, update docs

CHANGELOG.md

@@ -13,7 +13,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Changed
 - **BREAKING**: Split `BaseExtractionEngine.extract` into `extract` and `extract_artifacts` for consistency with `BaseSummaryEngine`.
 - **BREAKING**: `BaseExtractionEngine` no longer catches exceptions and returns `ErrorArtifact`s.
-- `JsonExtractionEngine` to extract either a JSON object or array depending on the provided schema. 
+- **BREAKING**: `JsonExtractionEngine.template_schema` is now required.
+- **BREAKING**: `CsvExtractionEngine.column_names` is now required.
 - `JsonExtractionEngine.extract_artifacts` now returns a `ListArtifact[JsonArtifact]`.
 - `CsvExtractionEngine.extract_artifacts` now returns a `ListArtifact[CsvRowArtifact]`.
 

docs/griptape-framework/engines/extraction-engines.md

@@ -10,10 +10,7 @@ As of now, Griptape supports two types of Extraction Engines: the CSV Extraction
 
 ## CSV
 
-The CSV Extraction Engine is designed specifically for extracting data from CSV-formatted content.
-
-!!! info
-    The CSV Extraction Engine requires the `column_names` parameter for specifying the columns to be extracted.
+The CSV Extraction Engine is designed for extracting CSV-formatted content from unstructured data.
 
 ```python
 --8<-- "docs/griptape-framework/engines/src/extraction_engines_1.py"
@@ -27,15 +24,27 @@ Charlie,40,Texas
 
 ## JSON
 
-The JSON Extraction Engine is tailored for extracting data from JSON-formatted content. 
+The JSON Extraction Engine is designed for extracting JSON-formatted content from unstructed data. 
 
-!!! info
-    The JSON Extraction Engine requires the `template_schema` parameter for specifying the structure to be extracted.
 
 ```python
 --8<-- "docs/griptape-framework/engines/src/extraction_engines_2.py"
 ```
 ```
-{'name': 'Alice', 'age': 28, 'location': 'New York'}
-{'name': 'Bob', 'age': 35, 'location': 'California'}
+{
+  "model": "GPT-3.5",
+  "notes": [
+    "Part of OpenAI's GPT series.",
+    "Used in ChatGPT and Microsoft Copilot."
+  ]
+}
+{
+  "model": "GPT-4",
+  "notes": [
+    "Part of OpenAI's GPT series.",
+    "Praised for increased accuracy and multimodal capabilities.",
+    "Architecture and number of parameters not revealed."
+  ]
+}
+...Output truncated for brevity...
 ```

docs/griptape-framework/engines/src/extraction_engines_2.py

@@ -1,24 +1,31 @@
-from schema import Schema
+import json
 
+from schema import Literal, Schema
+
+from griptape.artifacts import ErrorArtifact, ListArtifact
 from griptape.drivers import OpenAiChatPromptDriver
 from griptape.engines import JsonExtractionEngine
+from griptape.loaders import WebLoader
 
 # Define a schema for extraction
-user_schema = Schema([{"name": str, "age": int, "location": str}]).json_schema("UserSchema")
-
 json_engine = JsonExtractionEngine(
-    prompt_driver=OpenAiChatPromptDriver(model="gpt-3.5-turbo"), template_schema=user_schema
+    prompt_driver=OpenAiChatPromptDriver(model="gpt-4o"),
+    template_schema=Schema(
+        {
+            Literal("model", description="Name of an LLM model."): str,
+            Literal("notes", description="Any notes of substance about the model."): Schema([str]),
+        }
+    ).json_schema("ProductSchema"),
 )
 
-# Define some unstructured data
-sample_json_text = """
-Alice (Age 28) lives in New York.
-Bob (Age 35) lives in California.
-"""
+# Load data from the web
+web_data = WebLoader().load("https://en.wikipedia.org/wiki/Large_language_model")
 
+if isinstance(web_data, ErrorArtifact):
+    raise Exception(web_data.value)
 
 # Extract data using the engine
-result = json_engine.extract_text(sample_json_text)
+result = json_engine.extract_artifacts(ListArtifact(web_data))
 
 for artifact in result:
-    print(artifact.value)
+    print(json.dumps(artifact.value, indent=2))

docs/griptape-framework/structures/src/tasks_6.py

@@ -4,7 +4,9 @@
 from griptape.tasks import ExtractionTask
 
 # Instantiate the CSV extraction engine
-csv_extraction_engine = CsvExtractionEngine(prompt_driver=OpenAiChatPromptDriver(model="gpt-3.5-turbo"))
+csv_extraction_engine = CsvExtractionEngine(
+    prompt_driver=OpenAiChatPromptDriver(model="gpt-3.5-turbo"), column_names=["Name", "Age", "Address"]
+)
 
 # Define some unstructured data and columns
 csv_data = """
@@ -13,15 +15,12 @@
 Charlie is 40 and lives in Texas.
 """
 
-columns = ["Name", "Age", "Address"]
-
 
 # Create an agent and add the ExtractionTask to it
 agent = Agent()
 agent.add_task(
     ExtractionTask(
         extraction_engine=csv_extraction_engine,
-        args={"column_names": columns},
     )
 )
 

docs/griptape-framework/structures/src/tasks_7.py

@@ -8,20 +8,20 @@
 # Instantiate the json extraction engine
 json_extraction_engine = JsonExtractionEngine(
     prompt_driver=OpenAiChatPromptDriver(model="gpt-3.5-turbo"),
+    template_schema=Schema({"users": [{"name": str, "age": int, "location": str}]}).json_schema("UserSchema"),
 )
 
 # Define some unstructured data and a schema
 json_data = """
 Alice (Age 28) lives in New York.
 Bob (Age 35) lives in California.
 """
-user_schema = Schema({"users": [{"name": str, "age": int, "location": str}]}).json_schema("UserSchema")
+
 
 agent = Agent()
 agent.add_task(
     ExtractionTask(
         extraction_engine=json_extraction_engine,
-        args={"template_schema": user_schema},
     )
 )
 

griptape/artifacts/json_artifact.py

@@ -7,11 +7,11 @@
 
 from griptape.artifacts import BaseArtifact
 
-Json = Union[dict[str, "Json"], list["Json"], str, int, float, bool, None]
-
 
 @define
 class JsonArtifact(BaseArtifact):
+    Json = Union[dict[str, "Json"], list["Json"], str, int, float, bool, None]
+
     value: Json = field(converter=lambda v: json.loads(json.dumps(v)), metadata={"serializable": True})
 
     def to_text(self) -> str:

griptape/engines/extraction/csv_extraction_engine.py

@@ -17,7 +17,7 @@
 
 @define
 class CsvExtractionEngine(BaseExtractionEngine):
-    column_names: list[str] = field(default=Factory(list), kw_only=True)
+    column_names: list[str] = field(kw_only=True)
     system_template_generator: J2 = field(default=Factory(lambda: J2("engines/extraction/csv/system.j2")), kw_only=True)
     user_template_generator: J2 = field(default=Factory(lambda: J2("engines/extraction/csv/user.j2")), kw_only=True)
 

griptape/engines/extraction/json_extraction_engine.py

@@ -18,9 +18,9 @@
 
 @define
 class JsonExtractionEngine(BaseExtractionEngine):
-    JSON_PATTERN = r"(?s)(\{.*\}|\[.*\])"
+    JSON_PATTERN = r"(?s)[^\[]*(\[.*\])"
 
-    template_schema: dict = field(default=Factory(dict), kw_only=True)
+    template_schema: dict = field(kw_only=True)
     system_template_generator: J2 = field(
         default=Factory(lambda: J2("engines/extraction/json/system.j2")), kw_only=True
     )
@@ -42,7 +42,7 @@ def json_to_text_artifacts(self, json_input: str) -> list[JsonArtifact]:
         json_matches = re.findall(self.JSON_PATTERN, json_input, re.DOTALL)
 
         if json_matches:
-            return [JsonArtifact(json.loads(e)) for e in json_matches]
+            return [JsonArtifact(e) for e in json.loads(json_matches[-1])]
         else:
             return []
 

griptape/templates/engines/extraction/json/system.j2

@@ -1,5 +1,3 @@
-Your answer MUST be JSON that successfully validates against the Extraction Template JSON Schema.
-
 Extraction Template JSON Schema: """{{ json_template_schema }}"""
 
 {% if rulesets %}

griptape/templates/engines/extraction/json/user.j2

@@ -1,4 +1,4 @@
-Extract information from the Text.
+Extract information from the Text based on the Extraction Template JSON Schema into an array of JSON objects.
 Text: """{{ text }}"""
 
-JSON:
+JSON Array:

tests/unit/engines/extraction/test_json_extraction_engine.py

@@ -21,15 +21,16 @@ def engine(self):
     def test_extract_text(self, engine):
         result = engine.extract_text("foo")
 
-        assert len(result.value) == 1
-        assert result.value[0].value == [{"test_key_1": "test_value_1"}, {"test_key_2": "test_value_2"}]
+        assert len(result.value) == 2
+        assert result.value[0].value == {"test_key_1": "test_value_1"}
+        assert result.value[1].value == {"test_key_2": "test_value_2"}
 
     def test_chunked_extract_text(self, engine):
         large_text = Path(normpath(join(dirname(__file__), "../../../resources", "test.txt"))).read_text()
 
         extracted = engine.extract_text(large_text * 50)
-        assert len(extracted) == 177
-        assert extracted[0].value == [{"test_key_1": "test_value_1"}, {"test_key_2": "test_value_2"}]
+        assert len(extracted) == 354
+        assert extracted[0].value == {"test_key_1": "test_value_1"}
 
     def test_extract_error(self, engine):
         engine.template_schema = lambda: "non serializable"
@@ -38,7 +39,8 @@ def test_extract_error(self, engine):
 
     def test_json_to_text_artifacts(self, engine):
         extracted = engine.json_to_text_artifacts('[{"test_key_1": "test_value_1"}, {"test_key_2": "test_value_2"}]')
-        assert extracted[0].value == [{"test_key_1": "test_value_1"}, {"test_key_2": "test_value_2"}]
+        assert extracted[0].value == {"test_key_1": "test_value_1"}
+        assert extracted[1].value == {"test_key_2": "test_value_2"}
 
     def test_json_to_text_artifacts_no_matches(self, engine):
         assert engine.json_to_text_artifacts("asdfasdfasdf") == []

tests/unit/tools/test_extraction_tool.py

@@ -39,14 +39,16 @@ def test_json_extract_artifacts(self, json_tool):
             {"values": {"data": {"memory_name": json_tool.input_memory[0].name, "artifact_namespace": "foo"}}}
         )
 
-        assert len(result.value) == 1
-        assert result.value[0].value == [{"test_key_1": "test_value_1"}, {"test_key_2": "test_value_2"}]
+        assert len(result.value) == 2
+        assert result.value[0].value == {"test_key_1": "test_value_1"}
+        assert result.value[1].value == {"test_key_2": "test_value_2"}
 
     def test_json_extract_content(self, json_tool):
         result = json_tool.extract({"values": {"data": "foo"}})
 
-        assert len(result.value) == 1
-        assert result.value[0].value == [{"test_key_1": "test_value_1"}, {"test_key_2": "test_value_2"}]
+        assert len(result.value) == 2
+        assert result.value[0].value == {"test_key_1": "test_value_1"}
+        assert result.value[1].value == {"test_key_2": "test_value_2"}
 
     def test_csv_extract_artifacts(self, csv_tool):
         csv_tool.input_memory[0].store_artifact("foo", TextArtifact("foo,bar\nbaz,maz"))