feat: add functions to get context window overview

letta/agent.py

@@ -23,7 +23,7 @@
 from letta.interface import AgentInterface
 from letta.llm_api.helpers import is_context_overflow_error
 from letta.llm_api.llm_api_tools import create
-from letta.local_llm.utils import num_tokens_from_messages
+from letta.local_llm.utils import num_tokens_from_functions, num_tokens_from_messages
 from letta.memory import ArchivalMemory, RecallMemory, summarize_messages
 from letta.metadata import MetadataStore
 from letta.persistence_manager import LocalStateManager
@@ -33,6 +33,9 @@
 from letta.schemas.enums import MessageRole
 from letta.schemas.memory import ContextWindowOverview, Memory
 from letta.schemas.message import Message, UpdateMessage
+from letta.schemas.openai.chat_completion_request import (
+    Tool as ChatCompletionRequestTool,
+)
 from letta.schemas.openai.chat_completion_response import ChatCompletionResponse
 from letta.schemas.openai.chat_completion_response import (
     Message as ChatCompletionMessage,
@@ -1458,6 +1461,24 @@ def get_context_window(self) -> ContextWindowOverview:
         )
         num_tokens_external_memory_summary = count_tokens(external_memory_summary)
 
+        # tokens taken up by function definitions
+        if self.functions:
+            available_functions_definitions = [ChatCompletionRequestTool(type="function", function=f) for f in self.functions]
+            num_tokens_available_functions_definitions = num_tokens_from_functions(functions=self.functions, model=self.model)
+        else:
+            available_functions_definitions = []
+            num_tokens_available_functions_definitions = 0
+
+        num_tokens_used_total = (
+            num_tokens_system  # system prompt
+            + num_tokens_available_functions_definitions  # function definitions
+            + num_tokens_core_memory  # core memory
+            + num_tokens_external_memory_summary  # metadata (statistics) about recall/archival
+            + num_tokens_summary_memory  # summary of ongoing conversation
+            + num_tokens_messages  # tokens taken by messages
+        )
+        assert isinstance(num_tokens_used_total, int)
+
         return ContextWindowOverview(
             # context window breakdown (in messages)
             num_messages=len(self._messages),
@@ -1466,7 +1487,7 @@ def get_context_window(self) -> ContextWindowOverview:
             num_tokens_external_memory_summary=num_tokens_external_memory_summary,
             # top-level information
             context_window_size_max=self.agent_state.llm_config.context_window,
-            context_window_size_current=num_tokens_system + num_tokens_core_memory + num_tokens_summary_memory + num_tokens_messages,
+            context_window_size_current=num_tokens_used_total,
             # context window breakdown (in tokens)
             num_tokens_system=num_tokens_system,
             system_prompt=system_prompt,
@@ -1476,6 +1497,9 @@ def get_context_window(self) -> ContextWindowOverview:
             summary_memory=summary_memory,
             num_tokens_messages=num_tokens_messages,
             messages=self._messages,
+            # related to functions
+            num_tokens_functions_definitions=num_tokens_available_functions_definitions,
+            functions_definitions=available_functions_definitions,
         )
 
 

letta/llm_api/openai.py

@@ -18,8 +18,13 @@
 from letta.schemas.llm_config import LLMConfig
 from letta.schemas.message import Message as _Message
 from letta.schemas.message import MessageRole as _MessageRole
+from letta.schemas.openai.chat_completion_request import ChatCompletionRequest
 from letta.schemas.openai.chat_completion_request import (
-    ChatCompletionRequest,
+    FunctionCall as ToolFunctionChoiceFunctionCall,
+)
+from letta.schemas.openai.chat_completion_request import (
+    Tool,
+    ToolFunctionChoice,
     cast_message_to_subtype,
 )
 from letta.schemas.openai.chat_completion_response import (
@@ -100,10 +105,10 @@ def openai_get_model_list(
 
 def build_openai_chat_completions_request(
     llm_config: LLMConfig,
-    messages: List[Message],
+    messages: List[_Message],
     user_id: Optional[str],
     functions: Optional[list],
-    function_call: str,
+    function_call: Optional[str],
     use_tool_naming: bool,
     max_tokens: Optional[int],
 ) -> ChatCompletionRequest:
@@ -124,11 +129,17 @@ def build_openai_chat_completions_request(
         model = None
 
     if use_tool_naming:
+        if function_call is None:
+            tool_choice = None
+        elif function_call not in ["none", "auto", "required"]:
+            tool_choice = ToolFunctionChoice(type="function", function=ToolFunctionChoiceFunctionCall(name=function_call))
+        else:
+            tool_choice = function_call
         data = ChatCompletionRequest(
             model=model,
             messages=openai_message_list,
-            tools=[{"type": "function", "function": f} for f in functions] if functions else None,
-            tool_choice=function_call,
+            tools=[Tool(type="function", function=f) for f in functions] if functions else None,
+            tool_choice=tool_choice,
             user=str(user_id),
             max_tokens=max_tokens,
         )

letta/local_llm/utils.py

@@ -1,6 +1,6 @@
 import os
 import warnings
-from typing import List
+from typing import List, Union
 
 import requests
 import tiktoken
@@ -11,6 +11,7 @@
 import letta.local_llm.llm_chat_completion_wrappers.dolphin as dolphin
 import letta.local_llm.llm_chat_completion_wrappers.llama3 as llama3
 import letta.local_llm.llm_chat_completion_wrappers.zephyr as zephyr
+from letta.schemas.openai.chat_completion_request import Tool, ToolCall
 
 
 def post_json_auth_request(uri, json_payload, auth_type, auth_key):
@@ -123,7 +124,7 @@ def num_tokens_from_functions(functions: List[dict], model: str = "gpt-4"):
     return num_tokens
 
 
-def num_tokens_from_tool_calls(tool_calls: List[dict], model: str = "gpt-4"):
+def num_tokens_from_tool_calls(tool_calls: Union[List[dict], List[ToolCall]], model: str = "gpt-4"):
     """Based on above code (num_tokens_from_functions).
 
     Example to encode:
@@ -144,10 +145,25 @@ def num_tokens_from_tool_calls(tool_calls: List[dict], model: str = "gpt-4"):
 
     num_tokens = 0
     for tool_call in tool_calls:
-        function_tokens = len(encoding.encode(tool_call["id"]))
-        function_tokens += 2 + len(encoding.encode(tool_call["type"]))
-        function_tokens += 2 + len(encoding.encode(tool_call["function"]["name"]))
-        function_tokens += 2 + len(encoding.encode(tool_call["function"]["arguments"]))
+        if isinstance(tool_call, dict):
+            tool_call_id = tool_call["id"]
+            tool_call_type = tool_call["type"]
+            tool_call_function = tool_call["function"]
+            tool_call_function_name = tool_call_function["name"]
+            tool_call_function_arguments = tool_call_function["arguments"]
+        elif isinstance(tool_call, Tool):
+            tool_call_id = tool_call.id
+            tool_call_type = tool_call.type
+            tool_call_function = tool_call.function
+            tool_call_function_name = tool_call_function.name
+            tool_call_function_arguments = tool_call_function.arguments
+        else:
+            raise ValueError(f"Unknown tool call type: {type(tool_call)}")
+
+        function_tokens = len(encoding.encode(tool_call_id))
+        function_tokens += 2 + len(encoding.encode(tool_call_type))
+        function_tokens += 2 + len(encoding.encode(tool_call_function_name))
+        function_tokens += 2 + len(encoding.encode(tool_call_function_arguments))
 
         num_tokens += function_tokens
 

letta/schemas/memory.py

@@ -9,6 +9,7 @@
 
 from letta.schemas.block import Block
 from letta.schemas.message import Message
+from letta.schemas.openai.chat_completion_request import Tool
 
 
 class ContextWindowOverview(BaseModel):
@@ -41,6 +42,9 @@ class ContextWindowOverview(BaseModel):
     num_tokens_summary_memory: int = Field(..., description="The number of tokens in the summary memory.")
     summary_memory: Optional[str] = Field(None, description="The content of the summary memory.")
 
+    num_tokens_functions_definitions: int = Field(..., description="The number of tokens in the functions definitions.")
+    functions_definitions: Optional[List[Tool]] = Field(..., description="The content of the functions definitions.")
+
     num_tokens_messages: int = Field(..., description="The number of tokens in the messages list.")
     # TODO make list of messages?
     # messages: List[dict] = Field(..., description="The messages in the context window.")

letta/schemas/openai/chat_completion_request.py

@@ -74,7 +74,7 @@ class ToolFunctionChoice(BaseModel):
     function: FunctionCall
 
 
-ToolChoice = Union[Literal["none", "auto"], ToolFunctionChoice]
+ToolChoice = Union[Literal["none", "auto", "required"], ToolFunctionChoice]
 
 
 ## tools ##
@@ -117,7 +117,7 @@ class ChatCompletionRequest(BaseModel):
 
     # function-calling related
     tools: Optional[List[Tool]] = None
-    tool_choice: Optional[ToolChoice] = "none"
+    tool_choice: Optional[ToolChoice] = None  # "none" means don't call a tool
     # deprecated scheme
     functions: Optional[List[FunctionSchema]] = None
     function_call: Optional[FunctionCallChoice] = None

letta/server/server.py

@@ -73,7 +73,12 @@
 from letta.schemas.job import Job
 from letta.schemas.letta_message import LettaMessage
 from letta.schemas.llm_config import LLMConfig
-from letta.schemas.memory import ArchivalMemorySummary, Memory, RecallMemorySummary
+from letta.schemas.memory import (
+    ArchivalMemorySummary,
+    ContextWindowOverview,
+    Memory,
+    RecallMemorySummary,
+)
 from letta.schemas.message import Message, MessageCreate, MessageRole, UpdateMessage
 from letta.schemas.organization import Organization, OrganizationCreate
 from letta.schemas.passage import Passage
@@ -2166,3 +2171,12 @@ def add_llm_model(self, request: LLMConfig) -> LLMConfig:
 
     def add_embedding_model(self, request: EmbeddingConfig) -> EmbeddingConfig:
         """Add a new embedding model"""
+
+    def get_agent_context_window(
+        self,
+        user_id: str,
+        agent_id: str,
+    ) -> ContextWindowOverview:
+        # Get the current message
+        letta_agent = self._get_or_load_agent(agent_id=agent_id)
+        return letta_agent.get_context_window()

tests/test_server.py

@@ -507,3 +507,43 @@ def test_agent_rethink_rewrite_retry(server, user_id, agent_id):
     args_json = json.loads(last_agent_message.tool_calls[0].function.arguments)
     print(args_json)
     assert "message" in args_json and args_json["message"] is not None and args_json["message"] != new_text
+
+
+def test_get_context_window_overview(server: SyncServer, user_id: str, agent_id: str):
+    """Test that the context window overview fetch works"""
+
+    overview = server.get_agent_context_window(user_id=user_id, agent_id=agent_id)
+    assert overview is not None
+
+    # Run some basic checks
+    assert overview.context_window_size_max is not None
+    assert overview.context_window_size_current is not None
+    assert overview.num_archival_memory is not None
+    assert overview.num_recall_memory is not None
+    assert overview.num_tokens_external_memory_summary is not None
+    assert overview.num_tokens_system is not None
+    assert overview.system_prompt is not None
+    assert overview.num_tokens_core_memory is not None
+    assert overview.core_memory is not None
+    assert overview.num_tokens_summary_memory is not None
+    if overview.num_tokens_summary_memory > 0:
+        assert overview.summary_memory is not None
+    else:
+        assert overview.summary_memory is None
+    assert overview.num_tokens_functions_definitions is not None
+    if overview.num_tokens_functions_definitions > 0:
+        assert overview.functions_definitions is not None
+    else:
+        assert overview.functions_definitions is None
+    assert overview.num_tokens_messages is not None
+    assert overview.messages is not None
+
+    assert overview.context_window_size_max >= overview.context_window_size_current
+    assert overview.context_window_size_current == (
+        overview.num_tokens_system
+        + overview.num_tokens_core_memory
+        + overview.num_tokens_summary_memory
+        + overview.num_tokens_messages
+        + overview.num_tokens_functions_definitions
+        + overview.num_tokens_external_memory_summary
+    )