[CI] Expand test_guided_generate to test all backends

tests/entrypoints/llm/test_guided_generate.py

@@ -10,7 +10,8 @@
 from vllm.outputs import RequestOutput
 from vllm.sampling_params import GuidedDecodingParams, SamplingParams
 
-MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
+MODEL_NAME = "Qwen/Qwen2.5-7B-Instruct"
+GUIDED_DECODING_BACKENDS = ["outlines", "lm-format-enforcer", "xgrammar"]
 
 
 @pytest.fixture(scope="module")
@@ -26,11 +27,13 @@ def llm():
 
 
 @pytest.mark.skip_global_cleanup
-def test_guided_regex(sample_regex, llm):
-    sampling_params = SamplingParams(
-        temperature=0.8,
-        top_p=0.95,
-        guided_decoding=GuidedDecodingParams(regex=sample_regex))
+@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+def test_guided_regex(sample_regex, llm, guided_decoding_backend: str):
+    sampling_params = SamplingParams(temperature=0.8,
+                                     top_p=0.95,
+                                     guided_decoding=GuidedDecodingParams(
+                                         regex=sample_regex,
+                                         backend=guided_decoding_backend))
     outputs = llm.generate(prompts=[
         f"Give an example IPv4 address with this regex: {sample_regex}"
     ] * 2,
@@ -50,11 +53,14 @@ def test_guided_regex(sample_regex, llm):
 
 
 @pytest.mark.skip_global_cleanup
-def test_guided_json_completion(sample_json_schema, llm):
-    sampling_params = SamplingParams(
-        temperature=1.0,
-        max_tokens=1000,
-        guided_decoding=GuidedDecodingParams(json=sample_json_schema))
+@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+def test_guided_json_completion(sample_json_schema, llm,
+                                guided_decoding_backend: str):
+    sampling_params = SamplingParams(temperature=1.0,
+                                     max_tokens=1000,
+                                     guided_decoding=GuidedDecodingParams(
+                                         json=sample_json_schema,
+                                         backend=guided_decoding_backend))
     outputs = llm.generate(prompts=[
         f"Give an example JSON for an employee profile "
         f"that fits this schema: {sample_json_schema}"
@@ -77,11 +83,14 @@ def test_guided_json_completion(sample_json_schema, llm):
 
 
 @pytest.mark.skip_global_cleanup
-def test_guided_complex_json_completion(sample_complex_json_schema, llm):
-    sampling_params = SamplingParams(
-        temperature=1.0,
-        max_tokens=1000,
-        guided_decoding=GuidedDecodingParams(json=sample_complex_json_schema))
+@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+def test_guided_complex_json_completion(sample_complex_json_schema, llm,
+                                        guided_decoding_backend: str):
+    sampling_params = SamplingParams(temperature=1.0,
+                                     max_tokens=1000,
+                                     guided_decoding=GuidedDecodingParams(
+                                         json=sample_complex_json_schema,
+                                         backend=guided_decoding_backend))
     outputs = llm.generate(prompts=[
         f"Give an example JSON for an assignment grade "
         f"that fits this schema: {sample_complex_json_schema}"
@@ -105,11 +114,14 @@ def test_guided_complex_json_completion(sample_complex_json_schema, llm):
 
 
 @pytest.mark.skip_global_cleanup
-def test_guided_definition_json_completion(sample_definition_json_schema, llm):
+@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+def test_guided_definition_json_completion(sample_definition_json_schema, llm,
+                                           guided_decoding_backend: str):
     sampling_params = SamplingParams(temperature=1.0,
                                      max_tokens=1000,
                                      guided_decoding=GuidedDecodingParams(
-                                         json=sample_definition_json_schema))
+                                         json=sample_definition_json_schema,
+                                         backend=guided_decoding_backend))
     outputs = llm.generate(prompts=[
         f"Give an example JSON for solving 8x + 7 = -23 "
         f"that fits this schema: {sample_definition_json_schema}"
@@ -133,11 +145,14 @@ def test_guided_definition_json_completion(sample_definition_json_schema, llm):
 
 
 @pytest.mark.skip_global_cleanup
-def test_guided_choice_completion(sample_guided_choice, llm):
-    sampling_params = SamplingParams(
-        temperature=0.8,
-        top_p=0.95,
-        guided_decoding=GuidedDecodingParams(choice=sample_guided_choice))
+@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+def test_guided_choice_completion(sample_guided_choice, llm,
+                                  guided_decoding_backend: str):
+    sampling_params = SamplingParams(temperature=0.8,
+                                     top_p=0.95,
+                                     guided_decoding=GuidedDecodingParams(
+                                         choice=sample_guided_choice,
+                                         backend=guided_decoding_backend))
     outputs = llm.generate(
         prompts="The best language for type-safe systems programming is ",
         sampling_params=sampling_params,
@@ -156,13 +171,20 @@ def test_guided_choice_completion(sample_guided_choice, llm):
 
 
 @pytest.mark.skip_global_cleanup
-def test_guided_grammar(sample_sql_statements, llm):
-
-    sampling_params = SamplingParams(
-        temperature=0.8,
-        top_p=0.95,
-        max_tokens=1000,
-        guided_decoding=GuidedDecodingParams(grammar=sample_sql_statements))
+@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+def test_guided_grammar(sample_sql_statements, llm,
+                        guided_decoding_backend: str):
+    if guided_decoding_backend == "outlines":
+        pytest.skip("Outlines backend fails in this test case with:\n"
+                    "AttributeError: Error in model execution: 'ParserConf' "
+                    "object has no attribute 'deterministic'")
+
+    sampling_params = SamplingParams(temperature=0.8,
+                                     top_p=0.95,
+                                     max_tokens=1000,
+                                     guided_decoding=GuidedDecodingParams(
+                                         grammar=sample_sql_statements,
+                                         backend=guided_decoding_backend))
     outputs = llm.generate(
         prompts=("Generate a sql state that select col_1 from "
                  "table_1 where it is equals to 1"),
@@ -218,15 +240,18 @@ def test_validation_against_both_guided_decoding_options(sample_regex, llm):
 
 
 @pytest.mark.skip_global_cleanup
-def test_guided_json_object(llm):
-    sampling_params = SamplingParams(
-        temperature=1.0,
-        max_tokens=100,
-        guided_decoding=GuidedDecodingParams(json_object=True))
+@pytest.mark.parametrize("guided_decoding_backend", GUIDED_DECODING_BACKENDS)
+def test_guided_json_object(llm, guided_decoding_backend: str):
+    sampling_params = SamplingParams(temperature=1.0,
+                                     max_tokens=100,
+                                     n=2,
+                                     guided_decoding=GuidedDecodingParams(
+                                         json_object=True,
+                                         backend=guided_decoding_backend))
 
     outputs = llm.generate(
-        prompts=("Generate a JSON object describing a person with name "
-                 "and age for John Smith who is 31 years old."),
+        prompts=("Generate a JSON object with curly braces for a person with "
+                 "name and age fields for John Smith who is 31 years old."),
         sampling_params=sampling_params,
         use_tqdm=True)
 
@@ -235,10 +260,11 @@ def test_guided_json_object(llm):
         assert output is not None
         assert isinstance(output, RequestOutput)
 
-        generated_text = output.outputs[0].text
-        print(generated_text)
-        assert generated_text is not None
+        for i in range(2):
+            generated_text = output.outputs[i].text
+            print(generated_text)
+            assert generated_text is not None
 
-        # Parse to verify it is valid JSON
-        parsed_json = json.loads(generated_text)
-        assert isinstance(parsed_json, dict)
+            # Parse to verify it is valid JSON
+            parsed_json = json.loads(generated_text)
+            assert isinstance(parsed_json, dict)

tests/model_executor/test_guided_processors.py

@@ -13,6 +13,7 @@
 from vllm.sampling_params import GuidedDecodingParams
 
 MODEL_NAME = 'HuggingFaceH4/zephyr-7b-beta'
+GUIDED_DECODING_BACKENDS = ["outlines", "lm-format-enforcer", "xgrammar"]
 
 
 def test_guided_logits_processors(sample_regex, sample_json_schema):
@@ -42,8 +43,7 @@ def test_guided_logits_processors(sample_regex, sample_json_schema):
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize("backend",
-                         ["outlines", "lm-format-enforcer", "xgrammar"])
+@pytest.mark.parametrize("backend", GUIDED_DECODING_BACKENDS)
 @pytest.mark.parametrize("is_local", [True, False])
 async def test_guided_logits_processor_black_box(backend: str, is_local: bool,
                                                  sample_regex,

vllm/model_executor/guided_decoding/__init__.py

@@ -49,15 +49,60 @@ def check_object(obj: dict) -> bool:
     return check_object(schema)
 
 
+def has_lmf_unsupported_json_features(schema: dict) -> bool:
+    """
+    Check if JSON schema contains features unsupported 
+    by lm_format_enforcer.
+
+    Known issues:
+    - Regex patterns:
+        "grade": {
+            "type": "string",
+            "pattern": "^[A-D]$"  # Regex pattern
+        },
+    """
+
+    def check_object(obj: dict) -> bool:
+        if not isinstance(obj, dict):
+            return False
+
+        # Check for pattern restrictions
+        if "pattern" in obj:
+            return True
+
+        # Recursively check all nested objects and arrays
+        for value in obj.values():
+            if isinstance(value, dict):
+                if check_object(value):
+                    return True
+            elif isinstance(value, list):
+                for item in value:
+                    if isinstance(item, dict) and check_object(item):
+                        return True
+
+        return False
+
+    return check_object(schema)
+
+
 def maybe_backend_fallback(
         guided_params: GuidedDecodingParams) -> GuidedDecodingParams:
     # lm-format-enforce doesn't support grammar, fallback to xgrammar
-    if (guided_params.backend == "lm-format-enforcer"
-            and guided_params.grammar is not None):
-        logger.warning(
-            "lm-format-enforcer does not support grammar guided decoding. "
-            "Falling back to use xgrammar instead.")
-        guided_params.backend = "xgrammar"
+    if guided_params.backend == "lm-format-enforcer":
+        if guided_params.grammar is not None:
+            logger.warning(
+                "lm-format-enforcer does not support grammar guided decoding. "
+                "Falling back to use xgrammar instead.")
+            guided_params.backend = "xgrammar"
+
+        # lm-format-enforcer doesn't support some JSON schema features
+        elif (guided_params.json is not None
+              and has_lmf_unsupported_json_features(guided_params.json)):
+            logger.warning(
+                "lm-format-enforcer does not support advanced JSON schema "
+                "features like patterns or numeric ranges. "
+                "Falling back to use outlines instead.")
+            guided_params.backend = "outlines"
 
     if guided_params.backend == "xgrammar":
         # xgrammar only has x86 wheels for linux, fallback to outlines
@@ -82,6 +127,13 @@ def maybe_backend_fallback(
                 "Falling back to use outlines instead.")
             guided_params.backend = "outlines"
 
+    if (guided_params.backend == "outlines"
+            and guided_params.json_object is not None):
+        # outlines doesn't support json_object, fallback to xgrammar
+        logger.warning("outlines does not support json_object. "
+                       "Falling back to use xgrammar instead.")
+        guided_params.backend = "xgrammar"
+
     return guided_params