fix issue #237

adalflow/adalflow/core/generator.py

@@ -2,8 +2,9 @@
 
 It is a pipeline that consists of three subcomponents."""
 
-import os
 import json
+import re
+from pathlib import Path
 
 from typing import Any, Dict, Optional, Union, Callable, Tuple, List
 import logging
@@ -114,16 +115,14 @@ def __init__(
 
         template = template or DEFAULT_LIGHTRAG_SYSTEM_PROMPT
 
-        # Cache
-        model_str = (
-            f"{model_client.__class__.__name__}_{model_kwargs.get('model', 'default')}"
-        )
-        _cache_path = (
-            get_adalflow_default_root_path() if cache_path is None else cache_path
+        # create the cache path and initialize the cache engine
+
+        self.set_cache_path(
+            cache_path, model_client, model_kwargs.get("model", "default")
         )
-        self.cache_path = os.path.join(_cache_path, f"cache_{model_str}.db")
 
         CachedEngine.__init__(self, cache_path=self.cache_path)
+
         Component.__init__(self)
         GradComponent.__init__(self)
         CallbackManager.__init__(self)
@@ -148,7 +147,6 @@ def __init__(
         self.mock_output_data: str = "mock data"
         self.data_map_func: Callable = None
         self.set_data_map_func()
-        self.model_str = model_str
         self._use_cache = use_cache
 
         self._kwargs = {
@@ -163,6 +161,25 @@ def __init__(
         }
         self._teacher: Optional["Generator"] = None
 
+    def set_cache_path(self, cache_path: str, model_client: object, model: str):
+        """Set the cache path for the generator."""
+
+        # Construct a valid model string using the client class name and model
+        self.model_str = f"{model_client.__class__.__name__}_{model}"
+
+        # Remove any characters that are not allowed in file names (cross-platform)
+        # On Windows, characters like `:<>?/\|*` are prohibited.
+        self.model_str = re.sub(r"[^a-zA-Z0-9_\-]", "_", self.model_str)
+
+        _cache_path = (
+            get_adalflow_default_root_path() if cache_path is None else cache_path
+        )
+
+        # Use pathlib to handle paths more safely across OS
+        self.cache_path = Path(_cache_path) / f"cache_{self.model_str}.db"
+
+        log.debug(f"Cache path set to: {self.cache_path}")
+
     def get_cache_path(self) -> str:
         r"""Get the cache path for the generator."""
         return self.cache_path

adalflow/adalflow/utils/cache.py

@@ -1,5 +1,7 @@
 import hashlib
 import diskcache as dc
+from pathlib import Path
+from typing import Union
 
 
 def hash_text(text: str):
@@ -15,9 +17,11 @@ def direct(text: str):
 
 
 class CachedEngine:
-    def __init__(self, cache_path: str):
+    def __init__(self, cache_path: Union[str, Path]):
         super().__init__()
-        self.cache_path = cache_path
+        self.cache_path = Path(cache_path)
+        self.cache_path.parent.mkdir(parents=True, exist_ok=True)
+
         self.cache = dc.Cache(cache_path)
 
     def _check_cache(self, prompt: str):

adalflow/tests/test_generator.py

@@ -3,6 +3,7 @@
 import unittest
 import os
 import shutil
+from pathlib import Path
 
 from openai.types import CompletionUsage
 from openai.types.chat import ChatCompletion
@@ -55,6 +56,32 @@ def test_generator_call(self):
         print(f"output: {output}")
         # self.assertEqual(output.data, "Generated text response")
 
+    def test_cache_path(self):
+        prompt_kwargs = {"input_str": "Hello, world!"}
+        model_kwargs = {"model": "phi3.5:latest"}
+
+        self.test_generator = Generator(
+            model_client=self.mock_api_client,
+            prompt_kwargs=prompt_kwargs,
+            model_kwargs=model_kwargs,
+            use_cache=True,
+        )
+
+        # Convert the path to a string to avoid the TypeError
+        cache_path = self.test_generator.get_cache_path()
+        cache_path_str = str(cache_path)
+
+        print(f"cache path: {cache_path}")
+
+        # Check if the sanitized model string is in the cache path
+        self.assertIn("phi3_5_latest", cache_path_str)
+
+        # Check if the cache path exists as a file (or directory, depending on your use case)
+
+        self.assertTrue(
+            Path(cache_path).exists(), f"Cache path {cache_path_str} does not exist"
+        )
+
     def test_generator_prompt_logger_first_record(self):
         # prompt_kwargs = {"input_str": "Hello, world!"}
         # model_kwargs = {"model": "gpt-3.5-turbo"}