"""BasePrompt schema definition."""
from __future__ import annotations
import warnings
from abc import ABC
from string import Formatter
from typing import Any, Callable, Dict, List, Set, Tuple, Type
import langchain_core.utils.mustache as mustache
from langchain_core.prompt_values import PromptValue, StringPromptValue
from langchain_core.prompts.base import BasePromptTemplate
from langchain_core.pydantic_v1 import BaseModel, create_model
from langchain_core.utils import get_colored_text
from langchain_core.utils.formatting import formatter
from langchain_core.utils.interactive_env import is_interactive_env
[docs]
def validate_jinja2(template: str, input_variables: List[str]) -> None:
"""
Validate that the input variables are valid for the template.
Issues a warning if missing or extra variables are found.
Args:
template: The template string.
input_variables: The input variables.
"""
input_variables_set = set(input_variables)
valid_variables = _get_jinja2_variables_from_template(template)
missing_variables = valid_variables - input_variables_set
extra_variables = input_variables_set - valid_variables
warning_message = ""
if missing_variables:
warning_message += f"Missing variables: {missing_variables} "
if extra_variables:
warning_message += f"Extra variables: {extra_variables}"
if warning_message:
warnings.warn(warning_message.strip())
def _get_jinja2_variables_from_template(template: str) -> Set[str]:
try:
from jinja2 import Environment, meta
except ImportError:
raise ImportError(
"jinja2 not installed, which is needed to use the jinja2_formatter. "
"Please install it with `pip install jinja2`."
)
env = Environment()
ast = env.parse(template)
variables = meta.find_undeclared_variables(ast)
return variables
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def mustache_template_vars(
template: str,
) -> Set[str]:
"""Get the variables from a mustache template.
Args:
template: The template string.
Returns:
The variables from the template.
"""
vars: Set[str] = set()
section_depth = 0
for type, key in mustache.tokenize(template):
if type == "end":
section_depth -= 1
elif (
type in ("variable", "section", "inverted section", "no escape")
and key != "."
and section_depth == 0
):
vars.add(key.split(".")[0])
if type in ("section", "inverted section"):
section_depth += 1
return vars
Defs = Dict[str, "Defs"]
[docs]
def mustache_schema(
template: str,
) -> Type[BaseModel]:
"""Get the variables from a mustache template.
Args:
template: The template string.
Returns:
The variables from the template as a Pydantic model.
"""
fields = {}
prefix: Tuple[str, ...] = ()
section_stack: List[Tuple[str, ...]] = []
for type, key in mustache.tokenize(template):
if key == ".":
continue
if type == "end":
if section_stack:
prefix = section_stack.pop()
elif type in ("section", "inverted section"):
section_stack.append(prefix)
prefix = prefix + tuple(key.split("."))
fields[prefix] = False
elif type in ("variable", "no escape"):
fields[prefix + tuple(key.split("."))] = True
defs: Defs = {} # None means leaf node
while fields:
field, is_leaf = fields.popitem()
current = defs
for part in field[:-1]:
current = current.setdefault(part, {})
current.setdefault(field[-1], "" if is_leaf else {}) # type: ignore[arg-type]
return _create_model_recursive("PromptInput", defs)
def _create_model_recursive(name: str, defs: Defs) -> Type:
return create_model( # type: ignore[call-overload]
name,
**{
k: (_create_model_recursive(k, v), None) if v else (type(v), None)
for k, v in defs.items()
},
)
DEFAULT_FORMATTER_MAPPING: Dict[str, Callable] = {
"f-string": formatter.format,
"mustache": mustache_formatter,
"jinja2": jinja2_formatter,
}
DEFAULT_VALIDATOR_MAPPING: Dict[str, Callable] = {
"f-string": formatter.validate_input_variables,
"jinja2": validate_jinja2,
}
[docs]
def check_valid_template(
template: str, template_format: str, input_variables: List[str]
) -> None:
"""Check that template string is valid.
Args:
template: The template string.
template_format: The template format. Should be one of "f-string" or "jinja2".
input_variables: The input variables.
Raises:
ValueError: If the template format is not supported.
ValueError: If the prompt schema is invalid.
"""
try:
validator_func = DEFAULT_VALIDATOR_MAPPING[template_format]
except KeyError as exc:
raise ValueError(
f"Invalid template format {template_format!r}, should be one of"
f" {list(DEFAULT_FORMATTER_MAPPING)}."
) from exc
try:
validator_func(template, input_variables)
except (KeyError, IndexError) as exc:
raise ValueError(
"Invalid prompt schema; check for mismatched or missing input parameters"
f" from {input_variables}."
) from exc
[docs]
def get_template_variables(template: str, template_format: str) -> List[str]:
"""Get the variables from the template.
Args:
template: The template string.
template_format: The template format. Should be one of "f-string" or "jinja2".
Returns:
The variables from the template.
Raises:
ValueError: If the template format is not supported.
"""
if template_format == "jinja2":
# Get the variables for the template
input_variables = _get_jinja2_variables_from_template(template)
elif template_format == "f-string":
input_variables = {
v for _, v, _, _ in Formatter().parse(template) if v is not None
}
elif template_format == "mustache":
input_variables = mustache_template_vars(template)
else:
raise ValueError(f"Unsupported template format: {template_format}")
return sorted(input_variables)
[docs]
class StringPromptTemplate(BasePromptTemplate, ABC):
"""String prompt that exposes the format method, returning a prompt."""
@classmethod
def get_lc_namespace(cls) -> List[str]:
"""Get the namespace of the langchain object."""
return ["langchain", "prompts", "base"]
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def pretty_repr(self, html: bool = False) -> str:
"""Get a pretty representation of the prompt.
Args:
html: Whether to return an HTML-formatted string.
Returns:
A pretty representation of the prompt.
"""
# TODO: handle partials
dummy_vars = {
input_var: "{" + f"{input_var}" + "}" for input_var in self.input_variables
}
if html:
dummy_vars = {
k: get_colored_text(v, "yellow") for k, v in dummy_vars.items()
}
return self.format(**dummy_vars)
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def pretty_print(self) -> None:
"""Print a pretty representation of the prompt."""
print(self.pretty_repr(html=is_interactive_env())) # noqa: T201
