Support Python 3.8 (#29)

pyproject.toml

@@ -10,7 +10,7 @@ authors = [
 ]
 description = "RAGElo: A Tool for Evaluating Retrieval-Augmented Generation Models"
 readme = "README.md"
-requires-python = ">=3.10"
+requires-python = ">=3.8"
 license = { text = "Apache-2.0" }
 dynamic = ["version"]
 classifiers = [
@@ -38,7 +38,7 @@ dev = [
     "mypy==1.9.0",
     "Flake8-pyproject==1.2.3",
     "types-tqdm==4.66.0",
-    "pydantic==2.7.0",
+    "pydantic>=1.9.0",
     "pytest-asyncio==0.23.6",
     "pytest-mock==3.12.0",
 ]
@@ -58,7 +58,7 @@ profile = "black"
 
 [tool.mypy]
 plugins = ["pydantic.mypy"]
-python_version = "3.11"
+python_version = "3.8"
 show_column_numbers = true
 namespace_packages = true
 follow_imports = "silent"

ragelo/agent_rankers/base_agent_ranker.py

@@ -2,9 +2,8 @@
 
 import csv
 from collections import defaultdict
-from typing import Optional, Type, get_type_hints
+from typing import Dict, List, Optional, Tuple, Type, get_type_hints
 
-# from ragelo.agent_rankers import *
 from ragelo.logger import logger
 from ragelo.types import AgentRankerConfig
 from ragelo.types.types import Query
@@ -13,7 +12,7 @@
 
 class AgentRanker:
     config: AgentRankerConfig
-    ranking: defaultdict[str, list[str]]
+    ranking: Dict[str, List[str]]
     output_file: str = "agents_ranking.csv"
     name: str = "Agent Ranker"
 
@@ -28,17 +27,17 @@ def __init__(
 
     def run(
         self,
-        queries: Optional[list[Query]] = None,
+        queries: Optional[List[Query]] = None,
         evaluations_file: Optional[str] = None,
-    ) -> list[Query]:
+    ) -> List[Query]:
         """Compute score for each agent"""
         raise NotImplementedError
 
     def _prepare_queries(
         self,
-        queries: Optional[list[Query]] = None,
+        queries: Optional[List[Query]] = None,
         evaluations_file: Optional[str] = None,
-    ) -> list[Query]:
+    ) -> List[Query]:
         if queries is None:
             if evaluations_file is None:
                 raise ValueError(
@@ -53,7 +52,7 @@ def from_config(cls, config: AgentRankerConfig):
         # evaluations = cls.load_evaluations(config.evaluations_file)
         # return cls(config, evaluations)
 
-    def get_agents_ratings(self) -> dict[str, float]:
+    def get_agents_ratings(self) -> Dict[str, float]:
         """Returns the score of all players"""
         raise NotImplementedError
 
@@ -96,7 +95,7 @@ def print_ranking(self):
     def get_config_class(cls) -> Type[AgentRankerConfig]:
         return get_type_hints(cls)["config"]
 
-    def _flatten_evaluations(self, queries) -> list[tuple[str, str, str]]:
+    def _flatten_evaluations(self, queries) -> List[Tuple[str, str, str]]:
         evaluations = []
         for q in queries:
             for game in q.pairwise_games:
@@ -111,7 +110,7 @@ def _flatten_evaluations(self, queries) -> list[tuple[str, str, str]]:
 
 
 class AgentRankerFactory:
-    registry: dict[str, Type[AgentRanker]] = {}
+    registry: Dict[str, Type[AgentRanker]] = {}
 
     @classmethod
     def register(cls, name: str):

ragelo/agent_rankers/elo_ranker.py

@@ -1,5 +1,5 @@
 import random
-from typing import Optional
+from typing import Dict, List, Optional, Tuple
 
 from ragelo.agent_rankers.base_agent_ranker import AgentRanker, AgentRankerFactory
 from ragelo.logger import logger
@@ -19,21 +19,21 @@ def __init__(
         super().__init__(config)
         self.score_map = {"A": 1, "B": 0, "C": 0.5}
 
-        self.agents: dict[str, int] = {}
-        self.games: list[tuple[str, str, float]] = []
+        self.agents: Dict[str, int] = {}
+        self.games: List[Tuple[str, str, float]] = []
         self.computed = False
         self.initial_score = self.config.initial_score
         self.k = self.config.k
 
     def run(
         self,
-        queries: Optional[list[Query]] = None,
+        queries: Optional[List[Query]] = None,
         evaluations_file: Optional[str] = None,
     ):
         """Compute score for each agent"""
         queries = self._prepare_queries(queries, evaluations_file)
         self.evaluations = self._flatten_evaluations(queries)
-        agent_scores: dict[str, list[int]] = {}
+        agent_scores: Dict[str, List[int]] = {}
         for _ in range(self.config.rounds):
             self.games = self.__get_elo_scores()
             while self.games:
@@ -54,8 +54,8 @@ def get_agents_ratings(self):
             raise ValueError("Ranking not computed yet, Run evaluate() first")
         return self.agents
 
-    def __get_elo_scores(self) -> list[tuple[str, str, float]]:
-        games: list[tuple[str, str, float]] = []
+    def __get_elo_scores(self) -> List[Tuple[str, str, float]]:
+        games: List[Tuple[str, str, float]] = []
         for agent_a, agent_b, score in self.evaluations:
             score_val = self.score_map[score]
             games.append((agent_a, agent_b, score_val))

ragelo/cli/args.py

@@ -2,7 +2,7 @@
 
 import collections.abc
 import inspect
-from typing import Any, Callable, get_args, get_origin, get_type_hints
+from typing import Any, Callable, Dict, get_args, get_origin, get_type_hints
 
 from typer.models import ArgumentInfo, OptionInfo, ParameterInfo, ParamMeta
 
@@ -26,7 +26,7 @@ def callable(value: str):
     return value
 
 
-def get_params_from_function(func: Callable[..., Any]) -> dict[str, ParamMeta]:
+def get_params_from_function(func: Callable[..., Any]) -> Dict[str, ParamMeta]:
     signature = inspect.signature(func)
 
     type_hints = get_type_hints(func)