Updates to prompt for tool calls (#29)

* update system prompts to drop new line

* Add tool prompt formats

* support json format

* JSON in caps

* function_tag system prompt is also added as a user message

* added docstrings for ToolPromptFormat

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>

llama_toolchain/agentic_system/api/datatypes.py

@@ -110,6 +110,35 @@ class Session(BaseModel):
     started_at: datetime
 
 
+@json_schema_type
+class ToolPromptFormat(Enum):
+    """This Enum refers to the prompt format for calling zero shot tools
+
+    `json` --
+        Refers to the json format for calling tools.
+        The json format takes the form like
+        {
+            "type": "function",
+            "function" : {
+                "name": "function_name",
+                "description": "function_description",
+                "parameters": {...}
+            }
+        }
+
+    `function_tag` --
+        This is an example of how you could define
+        your own user defined format for making tool calls.
+        The function_tag format looks like this,
+        <function=function_name>(parameters)</function>
+
+    The detailed prompts for each of these formats are defined in `system_prompt.py`
+    """
+
+    json = "json"
+    function_tag = "function_tag"
+
+
 @json_schema_type
 class AgenticSystemInstanceConfig(BaseModel):
     instructions: str
@@ -127,6 +156,9 @@ class AgenticSystemInstanceConfig(BaseModel):
     # if you completely want to replace the messages prefixed by the system,
     # this is debug only
     debug_prefix_messages: Optional[List[Message]] = Field(default_factory=list)
+    tool_prompt_format: Optional[ToolPromptFormat] = Field(
+        default=ToolPromptFormat.json
+    )
 
 
 class AgenticSystemTurnResponseEventType(Enum):

llama_toolchain/agentic_system/client.py

@@ -13,8 +13,15 @@ import fire
 
 import httpx
 
-from llama_models.llama3_1.api.datatypes import BuiltinTool, SamplingParams
+from llama_models.llama3_1.api.datatypes import (
+    BuiltinTool,
+    SamplingParams,
+    ToolParamDefinition,
+    UserMessage,
+)
+from termcolor import cprint
 
+from llama_toolchain.agentic_system.event_logger import EventLogger
 from .api import (
     AgenticSystem,
     AgenticSystemCreateRequest,
@@ -25,6 +32,7 @@ from .api import (
     AgenticSystemToolDefinition,
     AgenticSystemTurnCreateRequest,
     AgenticSystemTurnResponseStreamChunk,
+    ToolPromptFormat,
 )
 
 
@@ -87,7 +95,7 @@ class AgenticSystemClient(AgenticSystem):
 
 async def run_main(host: str, port: int):
     # client to test remote impl of agentic system
-    api = await AgenticSystemClient(f"http://{host}:{port}")
+    api = AgenticSystemClient(f"http://{host}:{port}")
 
     tool_definitions = [
         AgenticSystemToolDefinition(
@@ -96,13 +104,28 @@ async def run_main(host: str, port: int):
         AgenticSystemToolDefinition(
             tool_name=BuiltinTool.wolfram_alpha,
         ),
-        AgenticSystemToolDefinition(
-            tool_name=BuiltinTool.photogen,
-        ),
         AgenticSystemToolDefinition(
             tool_name=BuiltinTool.code_interpreter,
         ),
     ]
+    tool_definitions += [
+        AgenticSystemToolDefinition(
+            tool_name="get_boiling_point",
+            description="Get the boiling point of a imaginary liquids (eg. polyjuice)",
+            parameters={
+                "liquid_name": ToolParamDefinition(
+                    param_type="str",
+                    description="The name of the liquid",
+                    required=True,
+                ),
+                "celcius": ToolParamDefinition(
+                    param_type="str",
+                    description="Whether to return the boiling point in Celcius",
+                    required=False,
+                ),
+            },
+        ),
+    ]
 
     create_request = AgenticSystemCreateRequest(
         model="Meta-Llama3.1-8B-Instruct",
@@ -114,12 +137,44 @@ async def run_main(host: str, port: int):
             output_shields=[],
             quantization_config=None,
             debug_prefix_messages=[],
+            tool_prompt_format=ToolPromptFormat.json,
         ),
     )
 
     create_response = await api.create_agentic_system(create_request)
     print(create_response)
-    # TODO: Add chat session / turn apis to test e2e
+
+    session_response = await api.create_agentic_system_session(
+        AgenticSystemSessionCreateRequest(
+            system_id=create_response.system_id,
+            session_name="test_session",
+        )
+    )
+    print(session_response)
+
+    user_prompts = [
+        "Who are you?",
+        "what is the 100th prime number?",
+        "Search web for who was 44th President of USA?",
+        "Write code to check if a number is prime. Use that to check if 7 is prime",
+        "What is the boiling point of polyjuicepotion ?",
+    ]
+    for content in user_prompts:
+        cprint(f"User> {content}", color="blue")
+        iterator = api.create_agentic_system_turn(
+            AgenticSystemTurnCreateRequest(
+                system_id=create_response.system_id,
+                session_id=session_response.session_id,
+                messages=[
+                    UserMessage(content=content),
+                ],
+                stream=True,
+            )
+        )
+
+        async for event, log in EventLogger().log(iterator):
+            if log is not None:
+                log.print()
 
 
 def main(host: str, port: int):

llama_toolchain/agentic_system/meta_reference/agent_instance.py

@@ -10,6 +10,8 @@ import uuid
 from datetime import datetime
 from typing import AsyncGenerator, List, Optional
 
+from termcolor import cprint
+
 from llama_toolchain.agentic_system.api.datatypes import (
     AgenticSystemInstanceConfig,
     AgenticSystemTurnResponseEvent,
@@ -24,6 +26,7 @@ from llama_toolchain.agentic_system.api.datatypes import (
     ShieldCallStep,
     StepType,
     ToolExecutionStep,
+    ToolPromptFormat,
     Turn,
 )
 
@@ -51,7 +54,6 @@ from llama_toolchain.safety.api.datatypes import (
     ShieldDefinition,
     ShieldResponse,
 )
-from termcolor import cprint
 from llama_toolchain.agentic_system.api.endpoints import *  # noqa
 
 from .safety import SafetyException, ShieldRunnerMixin
@@ -74,6 +76,7 @@ class AgentInstance(ShieldRunnerMixin):
         output_shields: List[ShieldDefinition],
         max_infer_iters: int = 10,
         prefix_messages: Optional[List[Message]] = None,
+        tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
     ):
         self.system_id = system_id
         self.instance_config = instance_config
@@ -86,7 +89,9 @@ class AgentInstance(ShieldRunnerMixin):
             self.prefix_messages = prefix_messages
         else:
             self.prefix_messages = get_agentic_prefix_messages(
-                builtin_tools, custom_tool_definitions
+                builtin_tools,
+                custom_tool_definitions,
+                tool_prompt_format,
             )
 
         for m in self.prefix_messages:

llama_toolchain/agentic_system/meta_reference/agentic_system.py

@@ -108,6 +108,7 @@ class MetaReferenceAgenticSystemImpl(AgenticSystem):
             input_shields=cfg.input_shields,
             output_shields=cfg.output_shields,
             prefix_messages=cfg.debug_prefix_messages,
+            tool_prompt_format=cfg.tool_prompt_format,
         )
 
         return AgenticSystemCreateResponse(

llama_toolchain/agentic_system/meta_reference/safety.py

@@ -6,14 +6,15 @@
 
 from typing import List
 
-from llama_models.llama3_1.api.datatypes import Message, Role
+from llama_models.llama3_1.api.datatypes import Message, Role, UserMessage
+from termcolor import cprint
+
 from llama_toolchain.safety.api.datatypes import (
     OnViolationAction,
     ShieldDefinition,
     ShieldResponse,
 )
 from llama_toolchain.safety.api.endpoints import RunShieldRequest, Safety
-from termcolor import cprint
 
 
 class SafetyException(Exception):  # noqa: N818
@@ -36,12 +37,11 @@ class ShieldRunnerMixin:
     async def run_shields(
         self, messages: List[Message], shields: List[ShieldDefinition]
     ) -> List[ShieldResponse]:
+        messages = messages.copy()
         # some shields like llama-guard require the first message to be a user message
         # since this might be a tool call, first role might not be user
         if len(messages) > 0 and messages[0].role != Role.user.value:
-            # TODO(ashwin): we need to change the type of the message, this kind of modification
-            # is no longer appropriate
-            messages[0].role = Role.user.value
+            messages[0] = UserMessage(content=messages[0].content)
 
         res = await self.safety_api.run_shields(
             RunShieldRequest(

llama_toolchain/agentic_system/meta_reference/system_prompt.py

@@ -5,21 +5,27 @@
 # the root directory of this source tree.
 
 import json
+import textwrap
 from datetime import datetime
 from typing import List
 
+from llama_toolchain.agentic_system.api.datatypes import ToolPromptFormat
+
 from llama_toolchain.inference.api import (
     BuiltinTool,
     Message,
     SystemMessage,
     ToolDefinition,
+    UserMessage,
 )
 
 from .tools.builtin import SingleMessageBuiltinTool
 
 
 def get_agentic_prefix_messages(
-    builtin_tools: List[SingleMessageBuiltinTool], custom_tools: List[ToolDefinition]
+    builtin_tools: List[SingleMessageBuiltinTool],
+    custom_tools: List[ToolDefinition],
+    tool_prompt_format: ToolPromptFormat,
 ) -> List[Message]:
     messages = []
     content = ""
@@ -34,28 +40,52 @@ def get_agentic_prefix_messages(
             ]
         )
         if tool_str:
-            content += f"Tools: {tool_str}\n"
+            content += f"Tools: {tool_str}"
 
     current_date = datetime.now()
     formatted_date = current_date.strftime("%d %B %Y")
     date_str = f"""
 Cutting Knowledge Date: December 2023
-Today Date: {formatted_date}\n\n"""
+Today Date: {formatted_date}\n"""
     content += date_str
+    messages.append(SystemMessage(content=content))
 
     if custom_tools:
-        custom_message = get_system_prompt_for_custom_tools(custom_tools)
-        content += custom_message
-
-    # TODO: Replace this hard coded message with instructions coming in the request
-    if False:
-        content += "You are a helpful Assistant."
-
+        if tool_prompt_format == ToolPromptFormat.function_tag:
+            text = prompt_for_function_tag(custom_tools)
+            messages.append(UserMessage(content=text))
+        elif tool_prompt_format == ToolPromptFormat.json:
+            text = prompt_for_json(custom_tools)
+            messages.append(UserMessage(content=text))
+        else:
+            raise NotImplementedError(
+                f"Tool prompt format {tool_prompt_format} is not supported"
+            )
+    else:
         messages.append(SystemMessage(content=content))
+
     return messages
 
 
-def get_system_prompt_for_custom_tools(custom_tools: List[ToolDefinition]) -> str:
+def prompt_for_json(custom_tools: List[ToolDefinition]) -> str:
+    tool_defs = "\n".join(
+        translate_custom_tool_definition_to_json(t) for t in custom_tools
+    )
+    content = textwrap.dedent(
+        """
+        Answer the user's question by making use of the following functions if needed.
+        If none of the function can be used, please say so.
+        Here is a list of functions in JSON format:
+        {tool_defs}
+
+        Return function calls in JSON format.
+        """
+    )
+    content = content.lstrip("\n").format(tool_defs=tool_defs)
+    return content
+
+
+def prompt_for_function_tag(custom_tools: List[ToolDefinition]) -> str:
     custom_tool_params = ""
     for t in custom_tools:
         custom_tool_params += get_instruction_string(t) + "\n"
@@ -76,7 +106,6 @@ Reminder:
 - Required parameters MUST be specified
 - Only call one function at a time
 - Put the entire function call reply on one line
-
 """
     return content
 
@@ -98,7 +127,6 @@ def get_parameters_string(custom_tool_definition) -> str:
     )
 
 
-# NOTE: Unused right now
 def translate_custom_tool_definition_to_json(tool_def):
     """Translates ToolDefinition to json as expected by model
     eg. output for a function
@@ -149,4 +177,4 @@ def translate_custom_tool_definition_to_json(tool_def):
     else:
         func_def["function"]["parameters"] = {}
 
-    return json.dumps(func_def)
+    return json.dumps(func_def, indent=4)

llama_toolchain/agentic_system/utils.py

@@ -15,6 +15,7 @@ from llama_toolchain.agentic_system.api import (
     AgenticSystemSessionCreateRequest,
     AgenticSystemToolDefinition,
 )
+from llama_toolchain.agentic_system.api.datatypes import ToolPromptFormat
 from llama_toolchain.agentic_system.client import AgenticSystemClient
 
 from llama_toolchain.agentic_system.tools.custom.execute import (
@@ -64,6 +65,7 @@ async def get_agent_system_instance(
     custom_tools: Optional[List[Any]] = None,
     disable_safety: bool = False,
     model: str = "Meta-Llama3.1-8B-Instruct",
+    tool_prompt_format: ToolPromptFormat = ToolPromptFormat.json,
 ) -> AgenticSystemClientWrapper:
     custom_tools = custom_tools or []
 
@@ -113,6 +115,7 @@ async def get_agent_system_instance(
                 ]
             ),
             sampling_params=SamplingParams(),
+            tool_prompt_format=tool_prompt_format,
         ),
     )
     create_response = await api.create_agentic_system(create_request)

llama_toolchain/safety/api/datatypes.py

@@ -8,12 +8,11 @@ from enum import Enum
 from typing import Dict, Optional, Union
 
 from llama_models.llama3_1.api.datatypes import ToolParamDefinition
-
 from llama_models.schema_utils import json_schema_type
 
-from llama_toolchain.common.deployment_types import RestAPIExecutionConfig
+from pydantic import BaseModel, validator
 
-from pydantic import BaseModel
+from llama_toolchain.common.deployment_types import RestAPIExecutionConfig
 
 
 @json_schema_type
@@ -43,6 +42,16 @@ class ShieldDefinition(BaseModel):
     on_violation_action: OnViolationAction = OnViolationAction.RAISE
     execution_config: Optional[RestAPIExecutionConfig] = None
 
+    @validator("shield_type", pre=True)
+    @classmethod
+    def validate_field(cls, v):
+        if isinstance(v, str):
+            try:
+                return BuiltinShield(v)
+            except ValueError:
+                return v
+        return v
+
 
 @json_schema_type
 class ShieldResponse(BaseModel):
@@ -51,3 +60,13 @@ class ShieldResponse(BaseModel):
     is_violation: bool
     violation_type: Optional[str] = None
     violation_return_message: Optional[str] = None
+
+    @validator("shield_type", pre=True)
+    @classmethod
+    def validate_field(cls, v):
+        if isinstance(v, str):
+            try:
+                return BuiltinShield(v)
+            except ValueError:
+                return v
+        return v