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/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
+        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))
 
-    # TODO: Replace this hard coded message with instructions coming in the request
-    if False:
-        content += "You are a helpful Assistant."
-
-    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)