BioMistral_gradio / llama-cpp-python /tests /test_llama_grammar.py
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import llama_cpp
import json
tree = """
leaf ::= "."
node ::= leaf | "(" node node ")"
root ::= node
"""
def test_grammar_from_string():
grammar = llama_cpp.LlamaGrammar.from_string(tree)
assert grammar._n_rules == 3
assert grammar._start_rule_index == 2
assert grammar.grammar is not None
def test_composed_pydantic_grammar():
"""
from pydantic import BaseModel
class A(BaseModel):
a: int
class B(BaseModel):
a: A
b: int
"""
# This schema corresponds to the grammar in the comment above.
# We don't use the pydantic models directly to avoid the dependency.
schema = {
"$defs": {
"A": {
"properties": {"a": {"title": "A", "type": "integer"}},
"required": ["a"],
"title": "A",
"type": "object",
}
},
"properties": {
"a": {"$ref": "#/$defs/A"},
"b": {"title": "B", "type": "integer"},
},
"required": ["a", "b"],
"title": "B",
"type": "object",
}
grammar = llama_cpp.LlamaGrammar.from_json_schema(json.dumps(schema))
assert grammar.grammar is not None
def test_grammar_anyof():
sch = {
"properties": {
"temperature": {
"description": "The temperature mentioned",
"type": "number",
},
"unit": {
"anyOf": [
{
"description": "Unit for temperature",
"enum": ["celsius", "fahrenheit"],
"type": "string",
},
{"type": "null"},
],
},
},
"type": "object",
}
grammar = llama_cpp.LlamaGrammar.from_json_schema(json.dumps(sch))
assert grammar.grammar is not None