Add regex dict: (#1616)

This class enables us to send a dictionary containing an output key and
the expected format, which in turn allows us to retrieve the result of
the matching formats and extract specific information from it.

To exclude irrelevant information from our return dictionary, we can
prompt the LLM to use a specific command that notifies us when it
doesn't know the answer. We refer to this variable as the
"no_update_value".

Regarding the updated regular expression pattern
(r"{}:\s?([^.'\n']*).?"), it enables us to retrieve a format as 'Output
Key':'value'.

We have improved the regex by adding an optional space between ':' and
'value' with "s?", and by excluding points and line jumps from the
matches using "[^.'\n']*".

langchain/output_parsers/__init__.py

@@ -4,10 +4,12 @@ from langchain.output_parsers.list import (
     ListOutputParser,
 )
 from langchain.output_parsers.regex import RegexParser
+from langchain.output_parsers.regex_dict import RegexDictParser
 from langchain.output_parsers.structured import ResponseSchema, StructuredOutputParser
 
 __all__ = [
     "RegexParser",
+    "RegexDictParser",
     "ListOutputParser",
     "CommaSeparatedListOutputParser",
     "BaseOutputParser",

langchain/output_parsers/regex_dict.py

@@ -0,0 +1,45 @@
+from __future__ import annotations
+
+import re
+from typing import Dict, Optional
+
+from pydantic import BaseModel
+
+from langchain.output_parsers.base import BaseOutputParser
+
+
+class RegexDictParser(BaseOutputParser, BaseModel):
+    """Class to parse the output into a dictionary."""
+
+    regex_pattern: str = r"{}:\s?([^.'\n']*)\.?"  # : :meta private:
+    output_key_to_format: Dict[str, str]
+    no_update_value: Optional[str] = None
+
+    @property
+    def _type(self) -> str:
+        """Return the type key."""
+        return "regex_dict_parser"
+
+    def parse(self, text: str) -> Dict[str, str]:
+        """Parse the output of an LLM call."""
+        result = {}
+        for output_key, expected_format in self.output_key_to_format.items():
+            specific_regex = self.regex_pattern.format(re.escape(expected_format))
+            matches = re.findall(specific_regex, text)
+            if not matches:
+                raise ValueError(
+                    f"No match found for output key: {output_key} with expected format \
+                        {expected_format} on text {text}"
+                )
+            elif len(matches) > 1:
+                raise ValueError(
+                    f"Multiple matches found for output key: {output_key} with \
+                        expected format {expected_format} on text {text}"
+                )
+            elif (
+                self.no_update_value is not None and matches[0] == self.no_update_value
+            ):
+                continue
+            else:
+                result[output_key] = matches[0]
+        return result

tests/unit_tests/output_parsers/test_regex_dict.py

@@ -0,0 +1,37 @@
+"""Test in memory docstore."""
+from langchain.output_parsers.regex_dict import RegexDictParser
+
+DEF_EXPECTED_RESULT = {"action": "Search", "action_input": "How to use this class?"}
+
+DEF_OUTPUT_KEY_TO_FORMAT = {"action": "Action", "action_input": "Action Input"}
+
+DEF_README = """We have just received a new result from the LLM, and our next step is
+to filter and read its format using regular expressions to identify specific fields,
+such as:
+
+- Action: Search
+- Action Input: How to use this class?
+- Additional Fields: "N/A"
+
+To assist us in this task, we use the regex_dict class. This class allows us to send a
+dictionary containing an output key and the expected format, which in turn enables us to
+retrieve the result of the matching formats and extract specific information from it.
+
+To exclude irrelevant information from our return dictionary, we can instruct the LLM to
+use a specific command that notifies us when it doesn't know the answer. We call this
+variable the "no_update_value", and for our current case, we set it to "N/A". Therefore,
+we expect the result to only contain the following fields:
+{
+ {key = action, value = search}
+ {key = action_input, value = "How to use this class?"}.
+}"""
+
+
+def test_regex_dict_result() -> None:
+    """Test regex dict result."""
+    regex_dict_parser = RegexDictParser(
+        output_key_to_format=DEF_OUTPUT_KEY_TO_FORMAT, no_update_value="N/A"
+    )
+    result_dict = regex_dict_parser.parse(DEF_README)
+    print("parse_result:", result_dict)
+    assert DEF_EXPECTED_RESULT == result_dict