Revert "PromptTemplate update documentation and expand kwargs (#8234)" (#8395)

fyi @eyurtsev was failing a unit test

libs/langchain/langchain/prompts/prompt.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 
 from pathlib import Path
 from string import Formatter
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, Dict, List, Union
 
 from pydantic import root_validator
 
@@ -16,24 +16,12 @@ from langchain.prompts.base import (
 
 
 class PromptTemplate(StringPromptTemplate):
-    """A prompt template for a language model.
+    """Schema to represent a prompt for an LLM.
-
-    A prompt template consists of a string template. It accepts a set of parameters
-    from the user that can be used to generate a prompt for a language model.
-
-    The template can be formatted using either f-strings (default) or jinja2 syntax.
 
     Example:
-
         .. code-block:: python
 
             from langchain import PromptTemplate
-
-            # Instantiation using from_template (recommended)
-            prompt = PromptTemplate.from_template("Say {foo}")
-            prompt.format(foo="bar")
-
-            # Instantiation using initializer
             prompt = PromptTemplate(input_variables=["foo"], template="Say {foo}")
     """
 
@@ -56,7 +44,6 @@ class PromptTemplate(StringPromptTemplate):
     """Whether or not to try validating the template."""
 
     def __add__(self, other: Any) -> PromptTemplate:
-        """Override the + operator to allow for combining prompt templates."""
         # Allow for easy combining
         if isinstance(other, PromptTemplate):
             if self.template_format != "f-string":
@@ -166,7 +153,6 @@ class PromptTemplate(StringPromptTemplate):
             template_file: The path to the file containing the prompt template.
             input_variables: A list of variable names the final prompt template
                 will expect.
-
         Returns:
             The prompt loaded from the file.
         """
@@ -175,52 +161,25 @@ class PromptTemplate(StringPromptTemplate):
         return cls(input_variables=input_variables, template=template, **kwargs)
 
     @classmethod
-    def from_template(
+    def from_template(cls, template: str, **kwargs: Any) -> PromptTemplate:
-        cls,
+        """Load a prompt template from a template."""
-        template: str,
+        if "template_format" in kwargs and kwargs["template_format"] == "jinja2":
-        *,
-        template_format: str = "f-string",
-        partial_variables: Optional[Dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> PromptTemplate:
-        """Load a prompt template from a template.
-
-        Args:
-            template: The template to load.
-            template_format: The format of the template. Use `jinja2` for jinja2,
-                             and `f-string` or None for f-strings.
-            partial_variables: A dictionary of variables that can be used to partially
-                               fill in the template. For example, if the template is
-                              `"{variable1} {variable2}"`, and `partial_variables` is
-                              `{"variable1": "foo"}`, then the final prompt will be
-                              `"foo {variable2}"`.
-
-        Returns:
-            The prompt template loaded from the template.
-        """
-        if template_format == "jinja2":
             # Get the variables for the template
             input_variables = _get_jinja2_variables_from_template(template)
-        elif template_format == "f-string":
+
+        else:
             input_variables = {
                 v for _, v, _, _ in Formatter().parse(template) if v is not None
             }
-        else:
-            raise ValueError(f"Unsupported template format: {template_format}")
 
-        _partial_variables = partial_variables or {}
+        if "partial_variables" in kwargs:
-
+            partial_variables = kwargs["partial_variables"]
-        if _partial_variables:
             input_variables = {
-                var for var in input_variables if var not in _partial_variables
+                var for var in input_variables if var not in partial_variables
             }
 
         return cls(
-            input_variables=sorted(input_variables),
+            input_variables=list(sorted(input_variables)), template=template, **kwargs
-            template=template,
-            template_format=template_format,
-            partial_variables=_partial_variables,
-            **kwargs,
         )
 
 

libs/langchain/tests/unit_tests/load/__snapshots__/test_dump.ambr

@@ -98,8 +98,7 @@
             "name"
           ],
           "template": "hello {name}!",
-          "template_format": "f-string",
+          "template_format": "f-string"
-          "partial_variables": {}
         }
       }
     }
@@ -177,8 +176,7 @@
                       "name"
                     ],
                     "template": "hello {name}!",
-                    "template_format": "f-string",
+                    "template_format": "f-string"
-                    "partial_variables": {}
                   }
                 }
               }
@@ -247,8 +245,7 @@
             "name"
           ],
           "template": "hello {name}!",
-          "template_format": "f-string",
+          "template_format": "f-string"
-          "partial_variables": {}
         }
       }
     }
@@ -280,25 +277,3 @@
   }
   '''
 # ---
-# name: test_serialize_prompt
-  '''
-  {
-    "lc": 1,
-    "type": "constructor",
-    "id": [
-      "langchain",
-      "prompts",
-      "prompt",
-      "PromptTemplate"
-    ],
-    "kwargs": {
-      "input_variables": [
-        "name"
-      ],
-      "template": "hello {name}!",
-      "template_format": "f-string",
-      "partial_variables": {}
-    }
-  }
-  '''
-# ---

libs/langchain/tests/unit_tests/load/test_dump.py

@@ -129,12 +129,6 @@ def test_serialize_llmchain_chat(snapshot: Any) -> None:
         del os.environ["OPENAI_API_KEY"]
 
 
-def test_serialize_prompt(snapshot: Any) -> None:
-    """Test that prompt is serialized correctly"""
-    prompt = PromptTemplate.from_template("hello {name}!")
-    assert dumps(prompt, pretty=True) == snapshot
-
-
 @pytest.mark.requires("openai")
 def test_serialize_llmchain_with_non_serializable_arg(snapshot: Any) -> None:
     llm = OpenAI(

libs/langchain/tests/unit_tests/prompts/test_prompt.py

@@ -161,10 +161,6 @@ Will it get confused{ }?
     )
     assert prompt == expected_prompt
 
-
-@pytest.mark.requires("jinja2")
-def test_prompt_from_jinja2_template_multiple_inputs() -> None:
-    """Test with multiple input variables."""
     # Multiple input variables.
     template = """\
 Hello world
@@ -190,10 +186,7 @@ You just set bar boolean variable to true
 
     assert prompt == expected_prompt
 
-
+    # Multiple input variables with repeats.
-@pytest.mark.requires("jinja2")
-def test_prompt_from_jinja2_template_multiple_inputs_with_repeats() -> None:
-    """Test with multiple input variables and repeats."""
     template = """\
 Hello world