Create test_structured_output_response_format_llama.py

analogous to integration-tests/models/test_grammar_response_format_llama.py

integration-tests/models/test_structured_output_response_format_llama.py

@@ -0,0 +1,102 @@
+import pytest
+import requests
+from pydantic import BaseModel
+from typing import List
+
+
+@pytest.fixture(scope="module")
+def llama_grammar_handle(launcher):
+    with launcher(
+        "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+        num_shard=1,
+        disable_grammar_support=False,
+        use_flash_attention=False,
+        max_batch_prefill_tokens=3000,
+    ) as handle:
+        yield handle
+
+
+@pytest.fixture(scope="module")
+async def llama_grammar(llama_grammar_handle):
+    await llama_grammar_handle.health(300)
+    return llama_grammar_handle.client
+
+
+@pytest.mark.release
+@pytest.mark.asyncio
+async def test_structured_output_response_format_llama_json(llama_grammar, response_snapshot):
+    class Weather(BaseModel):
+        unit: str
+        temperature: List[int]
+
+    # send the request
+    response = requests.post(
+        f"{llama_grammar.base_url}/v1/chat/completions",
+        headers=llama_grammar.headers,
+        json={
+            "model": "tgi",
+            "messages": [
+                {
+                    "role": "system",
+                    "content": f"Respond to the users questions and answer them in the following format: {Weather.schema()}",
+                },
+                {
+                    "role": "user",
+                    "content": "What's the weather like the next 3 days in San Francisco, CA?",
+                },
+            ],
+            "seed": 42,
+            "max_tokens": 500,
+            "response_format": {"type": "json_schema", "value": Weather.schema()},
+        },
+    )
+
+    chat_completion = response.json()
+    called = chat_completion["choices"][0]["message"]["content"]
+
+    assert response.status_code == 200
+    assert (
+        called
+        == '{\n  "temperature": [\n    35,\n    34,\n    36\n  ],\n  "unit": "°c"\n}'
+    )
+    assert chat_completion == response_snapshot
+
+
+@pytest.mark.release
+@pytest.mark.asyncio
+async def test_structured_output_response_format_llama_error_if_tools_not_installed(
+    llama_grammar,
+):
+    class Weather(BaseModel):
+        unit: str
+        temperature: List[int]
+
+    # send the request
+    response = requests.post(
+        f"{llama_grammar.base_url}/v1/chat/completions",
+        headers=llama_grammar.headers,
+        json={
+            "model": "tgi",
+            "messages": [
+                {
+                    "role": "system",
+                    "content": f"Respond to the users questions and answer them in the following format: {Weather.schema()}",
+                },
+                {
+                    "role": "user",
+                    "content": "What's the weather like the next 3 days in San Francisco, CA?",
+                },
+            ],
+            "seed": 42,
+            "max_tokens": 500,
+            "tools": [],
+            "response_format": {"type": "json_schema", "value": Weather.schema()},
+        },
+    )
+
+    # 422 means the server was unable to process the request because it contains invalid data.
+    assert response.status_code == 422
+    assert response.json() == {
+        "error": "Tool error: Grammar and tools are mutually exclusive",
+        "error_type": "tool_error",
+    }