Add a fake model that always returns the same canned response regardl…

…ess of what the prompt was.

While this behavior is technically achievable via the `StaticMapping` model, we can reduce the burden on the user to have to create the mapping of all `(prompt: canned_response)` pairs by making it into its own model.

PiperOrigin-RevId: 571449156

langfun/core/llms/fake.py

@@ -27,6 +27,19 @@ def _sample(self, prompts: list[lf.Message]) -> list[lf.LMSamplingResult]:
     ]
 
 
+@lf.use_init_args(['canned_response'])
+class StaticCannedResponse(lf.LanguageModel):
+  """Language model that always gives the same canned response."""
+
+  canned_response: Annotated[str, 'A canned response.']
+
+  def _sample(self, prompts: list[lf.Message]) -> list[lf.LMSamplingResult]:
+    return [
+        lf.LMSamplingResult([lf.LMSample(self.canned_response, 1.0)])
+        for _ in prompts
+    ]
+
+
 @lf.use_init_args(['mapping'])
 class StaticMapping(lf.LanguageModel):
   """A static mapping from prompt to response."""

langfun/core/llms/fake_test.py

@@ -17,22 +17,20 @@
 import io
 import unittest
 import langfun.core as lf
-from langfun.core.llms.fake import Echo
-from langfun.core.llms.fake import StaticMapping
-from langfun.core.llms.fake import StaticSequence
+from langfun.core.llms import fake as fakelm
 
 
 class EchoTest(unittest.TestCase):
 
   def test_sample(self):
-    lm = Echo()
+    lm = fakelm.Echo()
     self.assertEqual(
         lm.sample(['hi']), [lf.LMSamplingResult([lf.LMSample('hi', 1.0)])]
     )
 
   def test_call(self):
     string_io = io.StringIO()
-    lm = Echo(debug=True)
+    lm = fakelm.Echo(debug=True)
     with contextlib.redirect_stdout(string_io):
       self.assertEqual(lm('hi'), 'hi')
     debug_info = string_io.getvalue()
@@ -41,10 +39,38 @@ def test_call(self):
     self.assertIn('[0] LM RESPONSE', debug_info)
 
 
+class StaticCannedResponseTest(unittest.TestCase):
+
+  def test_sample(self):
+    canned_response = "I'm sorry, I can't help you with that."
+    lm = fakelm.StaticCannedResponse(canned_response)
+    self.assertEqual(
+        lm.sample(['hi']),
+        [lf.LMSamplingResult([lf.LMSample(canned_response, 1.0)])],
+    )
+    self.assertEqual(
+        lm.sample(['Tell me a joke.']),
+        [lf.LMSamplingResult([lf.LMSample(canned_response, 1.0)])],
+    )
+
+  def test_call(self):
+    string_io = io.StringIO()
+    canned_response = "I'm sorry, I can't help you with that."
+    lm = fakelm.StaticCannedResponse(canned_response, debug=True)
+
+    with contextlib.redirect_stdout(string_io):
+      self.assertEqual(lm('hi'), canned_response)
+
+    debug_info = string_io.getvalue()
+    self.assertIn('[0] LM INFO:', debug_info)
+    self.assertIn('[0] PROMPT SENT TO LM:', debug_info)
+    self.assertIn('[0] LM RESPONSE', debug_info)
+
+
 class StaticMappingTest(unittest.TestCase):
 
   def test_sample(self):
-    lm = StaticMapping({
+    lm = fakelm.StaticMapping({
         'Hi': 'Hello',
         'How are you?': 'I am fine, how about you?',
     }, temperature=0.5)
@@ -63,7 +89,7 @@ def test_sample(self):
 class StaticSequenceTest(unittest.TestCase):
 
   def test_sample(self):
-    lm = StaticSequence([
+    lm = fakelm.StaticSequence([
         'Hello',
         'I am fine, how about you?',
     ], temperature=0.5)