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# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import ast
from dataclasses import dataclass
from datetime import datetime
from typing import Any, Generator
from frame.clients import *
from frame.errands4 import Errand, default_errand_profile
from frame.routines import *
from frame.tidings import *
@dataclass
class FrameConfigV4:
long_context_cutoff: int = 8192
force_long_context: bool = False
max_iterations: int = 1024
interaction_level: str = "none" # one of "none", "system", "lm"
def update(self, **kwargs) -> None:
for key, value in kwargs.items():
if hasattr(self, key):
setattr(self, key, value)
def to_dict(self) -> dict:
return {
"long_context_cutoff": self.long_context_cutoff,
"force_long_context": self.force_long_context,
"max_iterations": self.max_iterations,
}
def from_dict(self, config: dict) -> None:
self.update(**config)
class SkillV4:
name: str
source_message: str
python_name: str
docstring: str
code: str
def __init__(
self,
name: str,
source_message: str,
python_name: str,
docstring: str,
code: str,
) -> None:
self.name = name
self.python_name = python_name
self.docstring = docstring
self.code = code
self.source_message = source_message
def to_dict(self) -> dict:
return {
"name": self.name,
"python_name": self.python_name,
"docstring": self.docstring,
"code": self.code,
"source_message": self.source_message,
}
def from_dict(self, skill: dict) -> None:
self.name = skill["name"]
self.python_name = skill["python_name"]
self.docstring = skill["docstring"]
self.code = skill["code"]
self.source_message = skill["source_message"]
def __str__(self) -> str:
return f"Skill: {self.name}\nPython name: {self.python_name}\nDocstring: {self.docstring}\nCode: {self.code}\nSource message: {self.source_message}"
class FrameV4:
# general
instance_id: str
config: FrameConfigV4
client_profile: dict[str, Client]
errand_profile: dict[str, type[Errand]]
compilation_trace: Trace
execution_trace: Trace
max_iterations: int = 1024
# skills
skills: dict[str, SkillV4]
# context
tidings: dict[str, Tiding]
globals: dict[str, Any]
last_mid: int
def __init__(
self,
client_profile: dict[str, Client] | Client,
instance_id: str | None = None,
config: FrameConfigV4 | None = None,
errand_profile: dict[str, type[Errand]] | None = None,
compilation_trace: bool | str | Trace | None = None,
execution_trace: bool | str | Trace | None = None,
) -> None:
self.instance_id = (
datetime.now().strftime("%Y%m%d_%H-%M-%S")
if instance_id is None
else instance_id
)
self.config = FrameConfigV4() if config is None else config
self.errand_profile = (
{**default_errand_profile, **errand_profile}
if errand_profile is not None
else {**default_errand_profile}
)
if isinstance(client_profile, Client):
self.client_profile = {
k: client_profile for k, _ in self.errand_profile.items()
}
elif isinstance(client_profile, dict):
self.client_profile = client_profile
else:
raise ValueError(f"Invalid client profile type: {type(client_profile)}")
self.compilation_trace = self.make_trace_from_arg(
path=f"./logs/{self.instance_id}_compilation.log",
trace_arg=compilation_trace,
)
self.execution_trace = self.make_trace_from_arg(
path=f"./logs/{self.instance_id}_execution.log", trace_arg=execution_trace
)
self.new_instance()
def get_chat_context_dict(self) -> dict:
"""
Returns the chat context as a dictionary
"""
filtered_system_globals = {
k: v
for k, v in self.globals.items()
if not k.startswith("__")
and not callable(v)
and type(v) in [float, int, str, bool, list, set, dict, tuple]
}
return {
"mid": self.last_mid,
"tidings": {k: v.to_dict() for k, v in self.tidings.items()},
"system_globals": filtered_system_globals,
}
def new_instance(self) -> None:
self.skills = {}
self.tidings = {}
self.globals = {"__messages": []}
self.last_mid = -1
exec("import math", {}, self.globals)
exec("from typing import *", {}, self.globals)
exec("from tavily import TavilyClient", {}, self.globals)
client = self.find_client_in_profile("language_model")
def language_model(prompt: str, pre_prompt: str = None) -> str:
"""
A simple language model calling function that returns the prompt as a response.
Use the following guidelines to create effective prompts when calling the function `language_model`:
- Start with using pre_prompt to assign a role to the language model (e.g. "You are an expert report writer." or "You are a Python code generator.")
- Begin the prompt by asking the language model to perform a specific task (e.g. "Write a report on the current state of AI research based on the following CONTEXT." or "Generate a Python function that behaviour described in ASSIGNMENT.")
- Mention the parameters of the prompt in the prompt, i.e. if the prompt operates on a text, mention the name of the parameter (e.g. "CONTEXT" or "ASSIGNMENT") and the type of the parameter (e.g. "text", "list", "dictionary", etc.).
- Specify the expected output format (e.g. "Write a report in Markdown format. Do not output any other text." or "Generate a Python function that returns a list of numbers and enclose it in ``` and ```. Any text outside the code block will be ignored.")
- Provide the context or assignment in a clear and concise manner (.e.g "\n\nCONTEXT:\n <context>" or "\n\nASSIGNMENT:\n<assignment>"); use newlines to separate the parameters from the rest of the prompt.
- If you think the prompt might get long once the parameters are pasted into it, add a list of reminders, e.g. "Reminders:\n- Do not output any other text.\n- Output a report in Markdown format based on the CONTEXT given..."
Args:
prompt (str): The prompt to be sent to the language model.
pre_prompt (str, optional): An optional pre-prompt (also known as system prompt, can be used to assign an overarching role to the LM) to be sent before the main prompt.
Returns:
str: The response from the language model.
"""
return client.run(pre_prompt, prompt)
if "language_model" not in self.skills:
self.skills["language_model"] = SkillV4(
name="language_model",
source_message="",
python_name="language_model",
docstring=language_model.__doc__,
code=language_model.__code__,
)
self.globals["language_model"] = language_model
self.execution_trace.write_separator()
self.execution_trace(
f"Creating new instance with id {self.instance_id} at {datetime.now()}"
)
self.execution_trace(
f"New instance created; skills, tidings, and globals erased"
)
self.execution_trace.write_separator()
# HIGH-LEVEL OUTPUT GENERATION CODE
def generate(
self, messages: list[dict], frame_config: FrameConfigV4 | None = None
) -> str:
"""
Generates a response to the given messages.
"""
if frame_config is None:
frame_config = self.config
last_msg = messages[-1]
ret = self.process_message(
mid=last_msg["mid"],
message=last_msg["content"],
message_type=last_msg["type"],
)
return ret
# HIGH-LEVEL OUTPUT GENERATION CODE
def generate_with_notifications(
self, messages: list[dict], frame_config: FrameConfigV4 | None = None
) -> Generator[dict, None, None]:
"""
Generates a response to the given messages.
"""
if frame_config is None:
frame_config = self.config
last_msg = messages[-1]
for notification in self.process_message(
mid=last_msg["mid"],
message=last_msg["content"],
message_type=last_msg["type"],
generate_not_return=True,
):
yield notification
# MESSAGE HANDLING
def process_message(
self,
mid: int,
message: str,
message_type: str | None,
generate_not_return: bool = False,
) -> Any | Generator[dict, None, None]:
"""
message_type is one of "routine", "routine_skill", "query", "query_skill", "code", "code_skill", "data", "auto" (also representable as None)
"""
if message.strip() == "":
raise ValueError("Empty message provided for instruction processing")
if message_type is None:
message_type = "auto"
self.allowed_message_types = [
"routine",
"routine_skill",
"query",
"query_skill",
"code",
"code_skill",
"data",
"auto",
"generating_routine",
]
if message_type not in self.allowed_message_types:
allowed_message_types_str: str = "', '".join(self.allowed_message_types)
raise ValueError(
f"Invalid message type: '{message_type}'; must be one of '{allowed_message_types_str}'"
)
if message_type == "auto":
message_type = self.decide_message_type(message)
skills: list[SkillV4] | None = None
invocation_code: str | None = None
variable_descriptions: dict[str, str] | None = None
if message_type == "code":
skills, invocation_code, variable_descriptions = self.process_message_code(
mid, message, self.tidings
)
elif message_type == "code_skill":
skills = self.process_message_code_skill(
mid, message
) # no tidings, skills are supposed to be pure functions
elif message_type == "routine":
skills, invocation_code, variable_descriptions = (
self.process_message_routine(mid, message, self.tidings)
)
elif message_type == "generating_routine":
if not generate_not_return:
raise ValueError(
"Generating routine messages must be processed with generate_not_return=True"
)
skills, invocation_code, variable_descriptions = (
self.process_message_routine(
mid, message, self.tidings, is_generating_routine=True
)
)
elif message_type == "data":
invocation_code = self.process_message_data(mid, message)
skills = []
else:
raise NotImplementedError(
f"Message type '{message_type}' not implemented yet"
)
self.log_compilation_result(mid, skills, invocation_code, variable_descriptions)
skill_capture_context = {}
for skill in skills:
exec(f"{skill.code}", self.globals, skill_capture_context)
self.skills[skill.name] = skill
for context_var, context_value in skill_capture_context.items():
if not context_var in self.globals:
self.globals[context_var] = context_value
execution_context = {
tiding.python_name: tiding.content for tiding in self.tidings.values()
}
__output = None
if invocation_code is not None:
if message_type != "generating_routine":
exec(invocation_code, self.globals, execution_context)
if "__output" in execution_context:
__output = execution_context["__output"]
if "__vars" in execution_context:
__vars = execution_context["__vars"]
for var_name, var_value in __vars.items():
self.tidings[var_name] = Tiding(
natural_name=var_name,
python_name=var_name,
content=var_value,
description=(
variable_descriptions[var_name]
if variable_descriptions is not None
and var_name in variable_descriptions
else ""
),
)
else:
exec(invocation_code, self.globals, execution_context)
__generator = execution_context["__generator"]
__final: dict[str, Any] = {}
for notification in __generator:
if notification["type"] == "final":
__final = notification
else:
yield notification
if "modified_vars" in __final:
for var_name, var_value in __final["modified_vars"].items():
self.tidings[var_name] = Tiding(
natural_name=var_name,
python_name=var_name,
content=var_value,
description=(
variable_descriptions[var_name]
if variable_descriptions is not None
and var_name in variable_descriptions
else ""
),
)
self.last_mid = mid
if not generate_not_return:
return __output
def decide_message_type(self, message: str) -> str:
"""
Decides the message type based on the content of the message.
Returns one of "routine", "routine_skill", "query", "query_skill", "code", "code_skill", "data"
"""
message_type_errand: Errand = self.find_errand_in_profile("message_type")()
message_type_client = self.find_client_in_profile("message_type")
message_type: str | None = message_type_errand.run(
runner=message_type_client,
args={"message": message},
)
if message_type is None or message_type not in self.allowed_message_types:
raise ValueError(
f"Message type could not be determined for message: '{message}'"
)
return message_type
# MESSAGE PROCESSING
def process_message_code(
self, mid: int, message: str, tidings: dict[str, Tiding]
) -> tuple[list[SkillV4], str | None, dict[str, str] | None]:
"""
Processes a code message and returns the corresponding skill(s), invocation code, and variable descriptions.
"""
code_processing_errand: Errand = self.find_errand_in_profile(
"message_code_processing"
)()
code_processing_client = self.find_client_in_profile("message_code_processing")
# serialize tidings for prompt injection
serialized_tidings = "\n".join(
[f"{k}: {v.content} # {v.description}" for k, v in tidings.items()]
)
code: str = code_processing_errand.run(
runner=code_processing_client,
args={"message": message, "tidings": serialized_tidings},
)
code = self.sanitize_code(code)
# replace the first occurence of code with f"message_{mid}_code"
code = code.replace("code", f"message_{mid}_code", 1)
docstring_addendum = f"\n\nThis function was generated to fulfill the intent of the user message with message id {mid}."
func_defs = self.extract_function_definitions(code)
skills = []
variable_descriptions: dict[str, str] | None = None
if func_defs:
func = func_defs[0]
func_code = func["code"].replace(
func["docstring"], func["docstring"] + docstring_addendum, 1
)
skills.append(
SkillV4(
name=func["python_name"],
source_message=message,
python_name=func["python_name"],
docstring=func["docstring"] + docstring_addendum,
code=func_code,
)
)
# TODO: perhaps, in the future, let the user know that other functions are present but ignored
message_code_call_errand: Errand = self.find_errand_in_profile(
"message_code_call"
)()
message_code_call_client = self.find_client_in_profile("message_code_call")
invocation_code = message_code_call_errand.run(
runner=message_code_call_client,
args={
"message": message,
"code": skills[0].code,
"tidings": serialized_tidings,
},
)
# Use MessageCodeVariablesErrand to get variable descriptions
message_code_variables_errand: Errand = self.find_errand_in_profile(
"message_code_variables"
)()
message_code_variables_client = self.find_client_in_profile(
"message_code_variables"
)
variable_descriptions_raw = message_code_variables_errand.run(
runner=message_code_variables_client,
args={
"message": message,
"code": skills[0].code,
"tidings": serialized_tidings,
},
)
# Parse the output into a dict
variable_descriptions = {}
for line in variable_descriptions_raw.strip().splitlines():
if "#" in line:
var, desc = line.split("#", 1)
variable_descriptions[var.strip()] = desc.strip()
return skills, invocation_code, variable_descriptions
else:
return [], None, None
def process_message_code_skill(self, mid: int, message: str) -> list[SkillV4]:
"""
Processes a code_skill message and returns the corresponding skill(s).
"""
code_skill_processing_errand: Errand = self.find_errand_in_profile(
"message_code_skill_processing"
)()
code_skill_processing_client = self.find_client_in_profile(
"message_code_skill_processing"
)
code: str = code_skill_processing_errand.run(
runner=code_skill_processing_client,
args={"message": message},
)
code = self.sanitize_code(code)
docstring_addendum = f"\n\nThis function was generated to fulfill the intent of the user message with message id {mid}."
func_defs = self.extract_function_definitions(code)
skills = []
if func_defs:
for func in func_defs:
func_code = func["code"].replace(
func["docstring"], func["docstring"] + docstring_addendum, 1
)
skills.append(
SkillV4(
name=func["python_name"],
source_message=message,
python_name=func["python_name"],
docstring=func["docstring"] + docstring_addendum,
code=func_code,
)
)
return skills
def process_message_routine(
self,
mid: int,
message: str,
tidings: dict[str, Tiding],
is_generating_routine: bool = False,
) -> tuple[list[SkillV4], str | None, dict[str, str] | None]:
"""
Processes a routine message and returns the corresponding skill(s), invocation code, and variable descriptions.
"""
routine_processing_errand: Errand = (
self.find_errand_in_profile("message_routine_processing")()
if not is_generating_routine
else self.find_errand_in_profile("message_generating_routine_processing")()
)
routine_processing_client = (
self.find_client_in_profile("message_routine_processing")
if not is_generating_routine
else self.find_client_in_profile("message_generating_routine_processing")
)
# Prepare skills and tidings for prompt injection
serialized_skills = "\n\n".join(
[f"function {k}\n---\n{v.docstring}" for k, v in self.skills.items()]
)
serialized_tidings = "\n".join(
[f"{k} = {v.content} # {v.description}" for k, v in tidings.items()]
)
code: str = routine_processing_errand.run(
runner=routine_processing_client,
args={
"message": message,
"skills": serialized_skills,
"tidings": serialized_tidings,
},
)
code = self.sanitize_code(code)
# replace the first occurrence of code with f"message_{mid}_routine_code"
code = code.replace("code", f"message_{mid}_routine_code", 1)
docstring_addendum = f"\n\nThis function was generated to fulfill the intent of the user message with message id {mid}."
func_defs = self.extract_function_definitions(code)
skills = []
variable_descriptions: dict[str, str] | None = None
if func_defs:
func = func_defs[0]
func_code = func["code"].replace(
func["docstring"], func["docstring"] + docstring_addendum, 1
)
skills.append(
SkillV4(
name=func["python_name"],
source_message=message,
python_name=func["python_name"],
docstring=func["docstring"] + docstring_addendum,
code=func_code,
)
)
# Generate invocation code using MessageRoutineCallErrand
message_routine_call_errand: Errand = (
self.find_errand_in_profile("message_routine_call")()
if not is_generating_routine
else self.find_errand_in_profile("message_generating_routine_call")()
)
message_routine_call_client = (
self.find_client_in_profile("message_routine_call")
if not is_generating_routine
else self.find_client_in_profile("message_generating_routine_call")
)
invocation_code = message_routine_call_errand.run(
runner=message_routine_call_client,
args={
"message": message,
"code": skills[0].code,
"tidings": serialized_tidings,
},
)
# Generate variable descriptions using MessageRoutineVariablesErrand
message_routine_variables_errand: Errand = self.find_errand_in_profile(
"message_routine_variables"
)()
message_routine_variables_client = self.find_client_in_profile(
"message_routine_variables"
)
variable_descriptions_raw = message_routine_variables_errand.run(
runner=message_routine_variables_client,
args={
"message": message,
"code": skills[0].code,
"tidings": serialized_tidings,
},
)
# Parse the output into a dict
variable_descriptions = {}
for line in variable_descriptions_raw.strip().splitlines():
if "#" in line:
var, desc = line.split("#", 1)
variable_descriptions[var.strip()] = desc.strip()
return skills, invocation_code, variable_descriptions
else:
return [], None, None
def process_message_data(self, mid: int, message: str) -> str:
"""
Processes a data message and returns the corresponding Python code that, when executed, loads variables into memory.
"""
data_processing_errand: Errand = self.find_errand_in_profile(
"message_data_processing"
)()
data_processing_client = self.find_client_in_profile("message_data_processing")
code: str = data_processing_errand.run(
runner=data_processing_client,
args={"message": message},
)
code = self.sanitize_code(code)
return code
# MISC
def make_trace_from_arg(
self, path: str, trace_arg: bool | str | Trace | None = None
) -> Trace:
if trace_arg is None:
return Trace(None)
if isinstance(trace_arg, Trace):
return trace_arg
if isinstance(trace_arg, bool):
if trace_arg is True:
return Trace(path)
else:
return Trace(None)
if isinstance(trace_arg, str):
if trace_arg == "stdout":
return Trace(None, copy_into_stdout=True)
if trace_arg == "file_and_stdout":
return Trace(path, copy_into_stdout=True)
else:
raise ValueError(f"Invalid value for trace: {trace_arg}")
def log_compilation_result(
self,
mid: int,
skills: list[SkillV4] | None,
invocation_code: str | None,
variable_descriptions: dict[str, str] | None,
) -> None:
self.compilation_trace.write_separator()
self.compilation_trace(f"Compiled message {mid} at {datetime.now()}")
if invocation_code is not None:
self.compilation_trace(f"Invocation code: {invocation_code}")
if variable_descriptions is not None:
self.compilation_trace(f"Variable descriptions: {variable_descriptions}")
if skills is not None:
for skill in skills:
self.compilation_trace("*" * 20)
self.compilation_trace(f"Skill name: {skill.name}")
self.compilation_trace(f"Python name: {skill.python_name}")
self.compilation_trace(f"Docstring:\n{skill.docstring}")
self.compilation_trace("-" * 20)
self.compilation_trace(f"Code:\n{skill.code}")
self.compilation_trace("-" * 20)
self.compilation_trace(f"Source message:\n{skill.source_message}")
self.compilation_trace.write_separator()
def find_errand_in_profile(self, designation: str) -> type[Errand]:
if designation in self.errand_profile:
return self.errand_profile[designation]
raise ValueError(
f"Errand choice with designation '{designation}' not found in the errand profile"
)
def find_client_in_profile(self, designation: str) -> Client:
if designation in self.client_profile:
return self.client_profile[designation]
raise ValueError(
f"Client choice with designation '{designation}' not found in the client profile"
)
def extract_function_definitions(self, code: str) -> list[dict[str, Any]]:
"""
Parses the given Python code and returns a list of dictionaries, each containing:
- python_name: the function name
- args: a list of argument names
- docstring: the function docstring (or None)
- code: the full source code of the function, including the signature
Only top-level (module-level) functions are extracted; nested functions are ignored.
"""
results = []
try:
tree = ast.parse(code)
except Exception as e:
return []
# Helper to get source code for a node
def get_source_segment(node):
try:
return ast.get_source_segment(code, node)
except Exception:
lines = code.splitlines()
if hasattr(node, "lineno") and hasattr(node, "end_lineno"):
return "\n".join(lines[node.lineno - 1 : node.end_lineno])
return None
# Only consider top-level functions (direct children of Module)
for node in tree.body:
if isinstance(node, ast.FunctionDef):
func_name = node.name
args = [arg.arg for arg in node.args.args]
docstring = ast.get_docstring(node)
func_code = get_source_segment(node)
results.append(
{
"python_name": func_name,
"args": args,
"docstring": docstring,
"code": func_code,
}
)
return results
def sanitize_code(self, code: str) -> str:
"""
Sanitizes the code by removing ```python and ``` tags. Note that the code might also start with ``` and end with ```.
"""
# Remove the first and last lines if they are empty
lines = code.splitlines()
if len(lines) > 0 and lines[0].strip() == "":
lines = lines[1:]
if len(lines) > 0 and lines[-1].strip() == "":
lines = lines[:-1]
# Remove the first and last lines if they are ```python or ```
if len(lines) > 0 and (
lines[0].strip() == "```python" or lines[0].strip() == "```"
):
lines = lines[1:]
if len(lines) > 0 and (
lines[-1].strip() == "```" or lines[-1].strip() == "```python"
):
lines = lines[:-1]
return "\n".join(lines)
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