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docs: document tool calls spec
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1 changed files with 71 additions and 6 deletions
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@ -54,7 +54,7 @@ Implement `POST /beta/litellm_basic_guardrail_api`
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{
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"texts": ["extracted text from the request"], // array of text strings
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"images": ["base64_encoded_image_data"], // optional array of images
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"tools": [ // optional array of tools (OpenAI ChatCompletionToolParam format)
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"tools": [ // optional array of tool definitions (OpenAI ChatCompletionToolParam format)
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{
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"type": "function",
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"function": {
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@ -69,6 +69,16 @@ Implement `POST /beta/litellm_basic_guardrail_api`
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}
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}
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],
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"tool_calls": [ // optional array of tool calls being invoked (OpenAI ChatCompletionMessageToolCall format)
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{
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"id": "call_abc123",
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"type": "function",
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"function": {
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"name": "get_weather",
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"arguments": "{\"location\": \"San Francisco\"}"
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}
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}
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],
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"structured_messages": [ // optional, full messages in OpenAI format (for chat endpoints)
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{"role": "system", "content": "You are a helpful assistant"},
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{"role": "user", "content": "Hello"}
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@ -141,8 +151,8 @@ The `tools` parameter provides information about available function/tool definit
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}
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```
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**Limitations:**
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- **Input only:** Tools are only passed for `input_type="request"` (pre-call guardrails). Output/response guardrails do not currently receive tool information.
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**Availability:**
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- **Input only:** Tools are only passed for `input_type="request"` (pre-call guardrails). Output/response guardrails do not currently receive tool definitions.
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- **Supported endpoints:** The `tools` parameter is supported on: `/v1/chat/completions`, `/v1/responses`, and `/v1/messages`. Other endpoints do not have tool support.
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**Use cases:**
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@ -151,6 +161,40 @@ The `tools` parameter provides information about available function/tool definit
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- Log tool usage for audit purposes
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- Block sensitive tools based on user context
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### `tool_calls` Parameter
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The `tool_calls` parameter contains actual function/tool invocations being made in the request or response.
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**Format:** OpenAI `ChatCompletionMessageToolCall` format (see [OpenAI API reference](https://platform.openai.com/docs/api-reference/chat/object#chat/object-tool_calls))
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**Example:**
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```json
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{
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"id": "call_abc123",
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"type": "function",
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"function": {
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"name": "get_weather",
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"arguments": "{\"location\": \"San Francisco\", \"unit\": \"celsius\"}"
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}
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}
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```
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**Key Difference from `tools`:**
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- **`tools`** = Tool definitions/schemas (what tools are *available*)
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- **`tool_calls`** = Tool invocations/executions (what tools are *being called* with what arguments)
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**Availability:**
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- **Both input and output:** Tool calls can be present in both `input_type="request"` (assistant messages requesting tool calls) and `input_type="response"` (LLM responses with tool calls).
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- **Supported endpoints:** The `tool_calls` parameter is supported on: `/v1/chat/completions`, `/v1/responses`, and `/v1/messages`.
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**Use cases:**
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- Validate tool call arguments before execution
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- Redact sensitive data from tool call arguments (e.g., PII)
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- Log tool invocations for audit/debugging
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- Block tool calls with dangerous parameters
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- Modify tool call arguments (e.g., enforce constraints, sanitize inputs)
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- Monitor tool usage patterns across users/teams
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### `structured_messages` Parameter
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The `structured_messages` parameter provides the full input in OpenAI chat completion spec format, useful for distinguishing between system and user messages.
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@ -237,7 +281,8 @@ app = FastAPI()
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class GuardrailRequest(BaseModel):
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texts: List[str]
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images: Optional[List[str]] = None
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tools: Optional[List[Dict[str, Any]]] = None # OpenAI ChatCompletionToolParam format
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tools: Optional[List[Dict[str, Any]]] = None # OpenAI ChatCompletionToolParam format (tool definitions)
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tool_calls: Optional[List[Dict[str, Any]]] = None # OpenAI ChatCompletionMessageToolCall format (tool invocations)
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structured_messages: Optional[List[Dict[str, Any]]] = None # OpenAI messages format (for chat endpoints)
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request_data: Dict[str, Any]
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input_type: str # "request" or "response"
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@ -263,18 +308,38 @@ async def apply_guardrail(request: GuardrailRequest):
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blocked_reason="Content contains prohibited terms"
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)
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# Example: Check tools (if present in request)
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# Example: Check tool definitions (if present in request)
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if request.tools:
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for tool in request.tools:
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if tool.get("type") == "function":
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function_name = tool.get("function", {}).get("name", "")
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# Block sensitive tools
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# Block sensitive tool definitions
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if function_name in ["delete_data", "access_admin_panel"]:
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return GuardrailResponse(
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action="BLOCKED",
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blocked_reason=f"Tool '{function_name}' is not allowed"
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)
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# Example: Check tool calls (if present in request or response)
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if request.tool_calls:
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for tool_call in request.tool_calls:
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if tool_call.get("type") == "function":
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function_name = tool_call.get("function", {}).get("name", "")
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arguments_str = tool_call.get("function", {}).get("arguments", "{}")
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# Parse arguments and validate
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import json
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try:
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arguments = json.loads(arguments_str)
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# Block dangerous arguments
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if "file_path" in arguments and ".." in str(arguments["file_path"]):
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return GuardrailResponse(
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action="BLOCKED",
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blocked_reason="Tool call contains path traversal attempt"
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)
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except json.JSONDecodeError:
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pass
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# Example: Check structured messages (if present in request)
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if request.structured_messages:
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for message in request.structured_messages:
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