Files
llmx/codex-rs/core/src/openai_tools.rs
Dylan 4ae6b9787a standardize shell description (#3514)
## Summary
Standardizes the shell description across sandbox_types, since we cover
this in the prompt, and have moved necessary details (like
network_access and writeable workspace roots) to EnvironmentContext
messages.

## Test Plan
- [x] updated unit tests
2025-09-12 14:24:09 -04:00

1152 lines
41 KiB
Rust
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use serde::Deserialize;
use serde::Serialize;
use serde_json::Value as JsonValue;
use serde_json::json;
use std::collections::BTreeMap;
use std::collections::HashMap;
use crate::model_family::ModelFamily;
use crate::plan_tool::PLAN_TOOL;
use crate::protocol::AskForApproval;
use crate::protocol::SandboxPolicy;
use crate::tool_apply_patch::ApplyPatchToolType;
use crate::tool_apply_patch::create_apply_patch_freeform_tool;
use crate::tool_apply_patch::create_apply_patch_json_tool;
#[derive(Debug, Clone, Serialize, PartialEq)]
pub struct ResponsesApiTool {
pub(crate) name: String,
pub(crate) description: String,
/// TODO: Validation. When strict is set to true, the JSON schema,
/// `required` and `additional_properties` must be present. All fields in
/// `properties` must be present in `required`.
pub(crate) strict: bool,
pub(crate) parameters: JsonSchema,
}
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub struct FreeformTool {
pub(crate) name: String,
pub(crate) description: String,
pub(crate) format: FreeformToolFormat,
}
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
pub struct FreeformToolFormat {
pub(crate) r#type: String,
pub(crate) syntax: String,
pub(crate) definition: String,
}
/// When serialized as JSON, this produces a valid "Tool" in the OpenAI
/// Responses API.
#[derive(Debug, Clone, Serialize, PartialEq)]
#[serde(tag = "type")]
pub(crate) enum OpenAiTool {
#[serde(rename = "function")]
Function(ResponsesApiTool),
#[serde(rename = "local_shell")]
LocalShell {},
// TODO: Understand why we get an error on web_search although the API docs say it's supported.
// https://platform.openai.com/docs/guides/tools-web-search?api-mode=responses#:~:text=%7B%20type%3A%20%22web_search%22%20%7D%2C
#[serde(rename = "web_search")]
WebSearch {},
#[serde(rename = "custom")]
Freeform(FreeformTool),
}
#[derive(Debug, Clone)]
pub enum ConfigShellToolType {
DefaultShell,
ShellWithRequest { sandbox_policy: SandboxPolicy },
LocalShell,
StreamableShell,
}
#[derive(Debug, Clone)]
pub(crate) struct ToolsConfig {
pub shell_type: ConfigShellToolType,
pub plan_tool: bool,
pub apply_patch_tool_type: Option<ApplyPatchToolType>,
pub web_search_request: bool,
pub include_view_image_tool: bool,
pub experimental_unified_exec_tool: bool,
}
pub(crate) struct ToolsConfigParams<'a> {
pub(crate) model_family: &'a ModelFamily,
pub(crate) approval_policy: AskForApproval,
pub(crate) sandbox_policy: SandboxPolicy,
pub(crate) include_plan_tool: bool,
pub(crate) include_apply_patch_tool: bool,
pub(crate) include_web_search_request: bool,
pub(crate) use_streamable_shell_tool: bool,
pub(crate) include_view_image_tool: bool,
pub(crate) experimental_unified_exec_tool: bool,
}
impl ToolsConfig {
pub fn new(params: &ToolsConfigParams) -> Self {
let ToolsConfigParams {
model_family,
approval_policy,
sandbox_policy,
include_plan_tool,
include_apply_patch_tool,
include_web_search_request,
use_streamable_shell_tool,
include_view_image_tool,
experimental_unified_exec_tool,
} = params;
let mut shell_type = if *use_streamable_shell_tool {
ConfigShellToolType::StreamableShell
} else if model_family.uses_local_shell_tool {
ConfigShellToolType::LocalShell
} else {
ConfigShellToolType::DefaultShell
};
if matches!(approval_policy, AskForApproval::OnRequest) && !use_streamable_shell_tool {
shell_type = ConfigShellToolType::ShellWithRequest {
sandbox_policy: sandbox_policy.clone(),
}
}
let apply_patch_tool_type = match model_family.apply_patch_tool_type {
Some(ApplyPatchToolType::Freeform) => Some(ApplyPatchToolType::Freeform),
Some(ApplyPatchToolType::Function) => Some(ApplyPatchToolType::Function),
None => {
if *include_apply_patch_tool {
Some(ApplyPatchToolType::Freeform)
} else {
None
}
}
};
Self {
shell_type,
plan_tool: *include_plan_tool,
apply_patch_tool_type,
web_search_request: *include_web_search_request,
include_view_image_tool: *include_view_image_tool,
experimental_unified_exec_tool: *experimental_unified_exec_tool,
}
}
}
/// Generic JSONSchema subset needed for our tool definitions
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq)]
#[serde(tag = "type", rename_all = "lowercase")]
pub(crate) enum JsonSchema {
Boolean {
#[serde(skip_serializing_if = "Option::is_none")]
description: Option<String>,
},
String {
#[serde(skip_serializing_if = "Option::is_none")]
description: Option<String>,
},
/// MCP schema allows "number" | "integer" for Number
#[serde(alias = "integer")]
Number {
#[serde(skip_serializing_if = "Option::is_none")]
description: Option<String>,
},
Array {
items: Box<JsonSchema>,
#[serde(skip_serializing_if = "Option::is_none")]
description: Option<String>,
},
Object {
properties: BTreeMap<String, JsonSchema>,
#[serde(skip_serializing_if = "Option::is_none")]
required: Option<Vec<String>>,
#[serde(
rename = "additionalProperties",
skip_serializing_if = "Option::is_none"
)]
additional_properties: Option<bool>,
},
}
fn create_shell_tool() -> OpenAiTool {
let mut properties = BTreeMap::new();
properties.insert(
"command".to_string(),
JsonSchema::Array {
items: Box::new(JsonSchema::String { description: None }),
description: Some("The command to execute".to_string()),
},
);
properties.insert(
"workdir".to_string(),
JsonSchema::String {
description: Some("The working directory to execute the command in".to_string()),
},
);
properties.insert(
"timeout_ms".to_string(),
JsonSchema::Number {
description: Some("The timeout for the command in milliseconds".to_string()),
},
);
OpenAiTool::Function(ResponsesApiTool {
name: "shell".to_string(),
description: "Runs a shell command and returns its output".to_string(),
strict: false,
parameters: JsonSchema::Object {
properties,
required: Some(vec!["command".to_string()]),
additional_properties: Some(false),
},
})
}
fn create_unified_exec_tool() -> OpenAiTool {
let mut properties = BTreeMap::new();
properties.insert(
"input".to_string(),
JsonSchema::Array {
items: Box::new(JsonSchema::String { description: None }),
description: Some(
"When no session_id is provided, treat the array as the command and arguments \
to launch. When session_id is set, concatenate the strings (in order) and write \
them to the session's stdin."
.to_string(),
),
},
);
properties.insert(
"session_id".to_string(),
JsonSchema::String {
description: Some(
"Identifier for an existing interactive session. If omitted, a new command \
is spawned."
.to_string(),
),
},
);
properties.insert(
"timeout_ms".to_string(),
JsonSchema::Number {
description: Some(
"Maximum time in milliseconds to wait for output after writing the input."
.to_string(),
),
},
);
OpenAiTool::Function(ResponsesApiTool {
name: "unified_exec".to_string(),
description:
"Runs a command in a PTY. Provide a session_id to reuse an existing interactive session.".to_string(),
strict: false,
parameters: JsonSchema::Object {
properties,
required: Some(vec!["input".to_string()]),
additional_properties: Some(false),
},
})
}
fn create_shell_tool_for_sandbox(sandbox_policy: &SandboxPolicy) -> OpenAiTool {
let mut properties = BTreeMap::new();
properties.insert(
"command".to_string(),
JsonSchema::Array {
items: Box::new(JsonSchema::String { description: None }),
description: Some("The command to execute".to_string()),
},
);
properties.insert(
"workdir".to_string(),
JsonSchema::String {
description: Some("The working directory to execute the command in".to_string()),
},
);
properties.insert(
"timeout_ms".to_string(),
JsonSchema::Number {
description: Some("The timeout for the command in milliseconds".to_string()),
},
);
if matches!(sandbox_policy, SandboxPolicy::WorkspaceWrite { .. }) {
properties.insert(
"with_escalated_permissions".to_string(),
JsonSchema::Boolean {
description: Some("Whether to request escalated permissions. Set to true if command needs to be run without sandbox restrictions".to_string()),
},
);
properties.insert(
"justification".to_string(),
JsonSchema::String {
description: Some("Only set if with_escalated_permissions is true. 1-sentence explanation of why we want to run this command.".to_string()),
},
);
}
OpenAiTool::Function(ResponsesApiTool {
name: "shell".to_string(),
description: "Runs a shell command and returns its output.".to_string(),
strict: false,
parameters: JsonSchema::Object {
properties,
required: Some(vec!["command".to_string()]),
additional_properties: Some(false),
},
})
}
fn create_view_image_tool() -> OpenAiTool {
// Support only local filesystem path.
let mut properties = BTreeMap::new();
properties.insert(
"path".to_string(),
JsonSchema::String {
description: Some("Local filesystem path to an image file".to_string()),
},
);
OpenAiTool::Function(ResponsesApiTool {
name: "view_image".to_string(),
description:
"Attach a local image (by filesystem path) to the conversation context for this turn."
.to_string(),
strict: false,
parameters: JsonSchema::Object {
properties,
required: Some(vec!["path".to_string()]),
additional_properties: Some(false),
},
})
}
/// TODO(dylan): deprecate once we get rid of json tool
#[derive(Serialize, Deserialize)]
pub(crate) struct ApplyPatchToolArgs {
pub(crate) input: String,
}
/// Returns JSON values that are compatible with Function Calling in the
/// Responses API:
/// https://platform.openai.com/docs/guides/function-calling?api-mode=responses
pub fn create_tools_json_for_responses_api(
tools: &Vec<OpenAiTool>,
) -> crate::error::Result<Vec<serde_json::Value>> {
let mut tools_json = Vec::new();
for tool in tools {
let json = serde_json::to_value(tool)?;
tools_json.push(json);
}
Ok(tools_json)
}
/// Returns JSON values that are compatible with Function Calling in the
/// Chat Completions API:
/// https://platform.openai.com/docs/guides/function-calling?api-mode=chat
pub(crate) fn create_tools_json_for_chat_completions_api(
tools: &Vec<OpenAiTool>,
) -> crate::error::Result<Vec<serde_json::Value>> {
// We start with the JSON for the Responses API and than rewrite it to match
// the chat completions tool call format.
let responses_api_tools_json = create_tools_json_for_responses_api(tools)?;
let tools_json = responses_api_tools_json
.into_iter()
.filter_map(|mut tool| {
if tool.get("type") != Some(&serde_json::Value::String("function".to_string())) {
return None;
}
if let Some(map) = tool.as_object_mut() {
// Remove "type" field as it is not needed in chat completions.
map.remove("type");
Some(json!({
"type": "function",
"function": map,
}))
} else {
None
}
})
.collect::<Vec<serde_json::Value>>();
Ok(tools_json)
}
pub(crate) fn mcp_tool_to_openai_tool(
fully_qualified_name: String,
tool: mcp_types::Tool,
) -> Result<ResponsesApiTool, serde_json::Error> {
let mcp_types::Tool {
description,
mut input_schema,
..
} = tool;
// OpenAI models mandate the "properties" field in the schema. The Agents
// SDK fixed this by inserting an empty object for "properties" if it is not
// already present https://github.com/openai/openai-agents-python/issues/449
// so here we do the same.
if input_schema.properties.is_none() {
input_schema.properties = Some(serde_json::Value::Object(serde_json::Map::new()));
}
// Serialize to a raw JSON value so we can sanitize schemas coming from MCP
// servers. Some servers omit the top-level or nested `type` in JSON
// Schemas (e.g. using enum/anyOf), or use unsupported variants like
// `integer`. Our internal JsonSchema is a small subset and requires
// `type`, so we coerce/sanitize here for compatibility.
let mut serialized_input_schema = serde_json::to_value(input_schema)?;
sanitize_json_schema(&mut serialized_input_schema);
let input_schema = serde_json::from_value::<JsonSchema>(serialized_input_schema)?;
Ok(ResponsesApiTool {
name: fully_qualified_name,
description: description.unwrap_or_default(),
strict: false,
parameters: input_schema,
})
}
/// Sanitize a JSON Schema (as serde_json::Value) so it can fit our limited
/// JsonSchema enum. This function:
/// - Ensures every schema object has a "type". If missing, infers it from
/// common keywords (properties => object, items => array, enum/const/format => string)
/// and otherwise defaults to "string".
/// - Fills required child fields (e.g. array items, object properties) with
/// permissive defaults when absent.
fn sanitize_json_schema(value: &mut JsonValue) {
match value {
JsonValue::Bool(_) => {
// JSON Schema boolean form: true/false. Coerce to an accept-all string.
*value = json!({ "type": "string" });
}
JsonValue::Array(arr) => {
for v in arr.iter_mut() {
sanitize_json_schema(v);
}
}
JsonValue::Object(map) => {
// First, recursively sanitize known nested schema holders
if let Some(props) = map.get_mut("properties")
&& let Some(props_map) = props.as_object_mut()
{
for (_k, v) in props_map.iter_mut() {
sanitize_json_schema(v);
}
}
if let Some(items) = map.get_mut("items") {
sanitize_json_schema(items);
}
// Some schemas use oneOf/anyOf/allOf - sanitize their entries
for combiner in ["oneOf", "anyOf", "allOf", "prefixItems"] {
if let Some(v) = map.get_mut(combiner) {
sanitize_json_schema(v);
}
}
// Normalize/ensure type
let mut ty = map
.get("type")
.and_then(|v| v.as_str())
.map(|s| s.to_string());
// If type is an array (union), pick first supported; else leave to inference
if ty.is_none()
&& let Some(JsonValue::Array(types)) = map.get("type")
{
for t in types {
if let Some(tt) = t.as_str()
&& matches!(
tt,
"object" | "array" | "string" | "number" | "integer" | "boolean"
)
{
ty = Some(tt.to_string());
break;
}
}
}
// Infer type if still missing
if ty.is_none() {
if map.contains_key("properties")
|| map.contains_key("required")
|| map.contains_key("additionalProperties")
{
ty = Some("object".to_string());
} else if map.contains_key("items") || map.contains_key("prefixItems") {
ty = Some("array".to_string());
} else if map.contains_key("enum")
|| map.contains_key("const")
|| map.contains_key("format")
{
ty = Some("string".to_string());
} else if map.contains_key("minimum")
|| map.contains_key("maximum")
|| map.contains_key("exclusiveMinimum")
|| map.contains_key("exclusiveMaximum")
|| map.contains_key("multipleOf")
{
ty = Some("number".to_string());
}
}
// If we still couldn't infer, default to string
let ty = ty.unwrap_or_else(|| "string".to_string());
map.insert("type".to_string(), JsonValue::String(ty.to_string()));
// Ensure object schemas have properties map
if ty == "object" {
if !map.contains_key("properties") {
map.insert(
"properties".to_string(),
JsonValue::Object(serde_json::Map::new()),
);
}
// If additionalProperties is an object schema, sanitize it too.
// Leave booleans as-is, since JSON Schema allows boolean here.
if let Some(ap) = map.get_mut("additionalProperties") {
let is_bool = matches!(ap, JsonValue::Bool(_));
if !is_bool {
sanitize_json_schema(ap);
}
}
}
// Ensure array schemas have items
if ty == "array" && !map.contains_key("items") {
map.insert("items".to_string(), json!({ "type": "string" }));
}
}
_ => {}
}
}
/// Returns a list of OpenAiTools based on the provided config and MCP tools.
/// Note that the keys of mcp_tools should be fully qualified names. See
/// [`McpConnectionManager`] for more details.
pub(crate) fn get_openai_tools(
config: &ToolsConfig,
mcp_tools: Option<HashMap<String, mcp_types::Tool>>,
) -> Vec<OpenAiTool> {
let mut tools: Vec<OpenAiTool> = Vec::new();
if config.experimental_unified_exec_tool {
tools.push(create_unified_exec_tool());
} else {
match &config.shell_type {
ConfigShellToolType::DefaultShell => {
tools.push(create_shell_tool());
}
ConfigShellToolType::ShellWithRequest { sandbox_policy } => {
tools.push(create_shell_tool_for_sandbox(sandbox_policy));
}
ConfigShellToolType::LocalShell => {
tools.push(OpenAiTool::LocalShell {});
}
ConfigShellToolType::StreamableShell => {
tools.push(OpenAiTool::Function(
crate::exec_command::create_exec_command_tool_for_responses_api(),
));
tools.push(OpenAiTool::Function(
crate::exec_command::create_write_stdin_tool_for_responses_api(),
));
}
}
}
if config.plan_tool {
tools.push(PLAN_TOOL.clone());
}
if let Some(apply_patch_tool_type) = &config.apply_patch_tool_type {
match apply_patch_tool_type {
ApplyPatchToolType::Freeform => {
tools.push(create_apply_patch_freeform_tool());
}
ApplyPatchToolType::Function => {
tools.push(create_apply_patch_json_tool());
}
}
}
if config.web_search_request {
tools.push(OpenAiTool::WebSearch {});
}
// Include the view_image tool so the agent can attach images to context.
if config.include_view_image_tool {
tools.push(create_view_image_tool());
}
if let Some(mcp_tools) = mcp_tools {
// Ensure deterministic ordering to maximize prompt cache hits.
let mut entries: Vec<(String, mcp_types::Tool)> = mcp_tools.into_iter().collect();
entries.sort_by(|a, b| a.0.cmp(&b.0));
for (name, tool) in entries.into_iter() {
match mcp_tool_to_openai_tool(name.clone(), tool.clone()) {
Ok(converted_tool) => tools.push(OpenAiTool::Function(converted_tool)),
Err(e) => {
tracing::error!("Failed to convert {name:?} MCP tool to OpenAI tool: {e:?}");
}
}
}
}
tools
}
#[cfg(test)]
mod tests {
use crate::model_family::find_family_for_model;
use mcp_types::ToolInputSchema;
use pretty_assertions::assert_eq;
use super::*;
fn assert_eq_tool_names(tools: &[OpenAiTool], expected_names: &[&str]) {
let tool_names = tools
.iter()
.map(|tool| match tool {
OpenAiTool::Function(ResponsesApiTool { name, .. }) => name,
OpenAiTool::LocalShell {} => "local_shell",
OpenAiTool::WebSearch {} => "web_search",
OpenAiTool::Freeform(FreeformTool { name, .. }) => name,
})
.collect::<Vec<_>>();
assert_eq!(
tool_names.len(),
expected_names.len(),
"tool_name mismatch, {tool_names:?}, {expected_names:?}",
);
for (name, expected_name) in tool_names.iter().zip(expected_names.iter()) {
assert_eq!(
name, expected_name,
"tool_name mismatch, {name:?}, {expected_name:?}"
);
}
}
#[test]
fn test_get_openai_tools() {
let model_family = find_family_for_model("codex-mini-latest")
.expect("codex-mini-latest should be a valid model family");
let config = ToolsConfig::new(&ToolsConfigParams {
model_family: &model_family,
approval_policy: AskForApproval::Never,
sandbox_policy: SandboxPolicy::ReadOnly,
include_plan_tool: true,
include_apply_patch_tool: false,
include_web_search_request: true,
use_streamable_shell_tool: false,
include_view_image_tool: true,
experimental_unified_exec_tool: true,
});
let tools = get_openai_tools(&config, Some(HashMap::new()));
assert_eq_tool_names(
&tools,
&["unified_exec", "update_plan", "web_search", "view_image"],
);
}
#[test]
fn test_get_openai_tools_default_shell() {
let model_family = find_family_for_model("o3").expect("o3 should be a valid model family");
let config = ToolsConfig::new(&ToolsConfigParams {
model_family: &model_family,
approval_policy: AskForApproval::Never,
sandbox_policy: SandboxPolicy::ReadOnly,
include_plan_tool: true,
include_apply_patch_tool: false,
include_web_search_request: true,
use_streamable_shell_tool: false,
include_view_image_tool: true,
experimental_unified_exec_tool: true,
});
let tools = get_openai_tools(&config, Some(HashMap::new()));
assert_eq_tool_names(
&tools,
&["unified_exec", "update_plan", "web_search", "view_image"],
);
}
#[test]
fn test_get_openai_tools_mcp_tools() {
let model_family = find_family_for_model("o3").expect("o3 should be a valid model family");
let config = ToolsConfig::new(&ToolsConfigParams {
model_family: &model_family,
approval_policy: AskForApproval::Never,
sandbox_policy: SandboxPolicy::ReadOnly,
include_plan_tool: false,
include_apply_patch_tool: false,
include_web_search_request: true,
use_streamable_shell_tool: false,
include_view_image_tool: true,
experimental_unified_exec_tool: true,
});
let tools = get_openai_tools(
&config,
Some(HashMap::from([(
"test_server/do_something_cool".to_string(),
mcp_types::Tool {
name: "do_something_cool".to_string(),
input_schema: ToolInputSchema {
properties: Some(serde_json::json!({
"string_argument": {
"type": "string",
},
"number_argument": {
"type": "number",
},
"object_argument": {
"type": "object",
"properties": {
"string_property": { "type": "string" },
"number_property": { "type": "number" },
},
"required": [
"string_property",
"number_property",
],
"additionalProperties": Some(false),
},
})),
required: None,
r#type: "object".to_string(),
},
output_schema: None,
title: None,
annotations: None,
description: Some("Do something cool".to_string()),
},
)])),
);
assert_eq_tool_names(
&tools,
&[
"unified_exec",
"web_search",
"view_image",
"test_server/do_something_cool",
],
);
assert_eq!(
tools[3],
OpenAiTool::Function(ResponsesApiTool {
name: "test_server/do_something_cool".to_string(),
parameters: JsonSchema::Object {
properties: BTreeMap::from([
(
"string_argument".to_string(),
JsonSchema::String { description: None }
),
(
"number_argument".to_string(),
JsonSchema::Number { description: None }
),
(
"object_argument".to_string(),
JsonSchema::Object {
properties: BTreeMap::from([
(
"string_property".to_string(),
JsonSchema::String { description: None }
),
(
"number_property".to_string(),
JsonSchema::Number { description: None }
),
]),
required: Some(vec![
"string_property".to_string(),
"number_property".to_string(),
]),
additional_properties: Some(false),
},
),
]),
required: None,
additional_properties: None,
},
description: "Do something cool".to_string(),
strict: false,
})
);
}
#[test]
fn test_get_openai_tools_mcp_tools_sorted_by_name() {
let model_family = find_family_for_model("o3").expect("o3 should be a valid model family");
let config = ToolsConfig::new(&ToolsConfigParams {
model_family: &model_family,
approval_policy: AskForApproval::Never,
sandbox_policy: SandboxPolicy::ReadOnly,
include_plan_tool: false,
include_apply_patch_tool: false,
include_web_search_request: false,
use_streamable_shell_tool: false,
include_view_image_tool: true,
experimental_unified_exec_tool: true,
});
// Intentionally construct a map with keys that would sort alphabetically.
let tools_map: HashMap<String, mcp_types::Tool> = HashMap::from([
(
"test_server/do".to_string(),
mcp_types::Tool {
name: "a".to_string(),
input_schema: ToolInputSchema {
properties: Some(serde_json::json!({})),
required: None,
r#type: "object".to_string(),
},
output_schema: None,
title: None,
annotations: None,
description: Some("a".to_string()),
},
),
(
"test_server/something".to_string(),
mcp_types::Tool {
name: "b".to_string(),
input_schema: ToolInputSchema {
properties: Some(serde_json::json!({})),
required: None,
r#type: "object".to_string(),
},
output_schema: None,
title: None,
annotations: None,
description: Some("b".to_string()),
},
),
(
"test_server/cool".to_string(),
mcp_types::Tool {
name: "c".to_string(),
input_schema: ToolInputSchema {
properties: Some(serde_json::json!({})),
required: None,
r#type: "object".to_string(),
},
output_schema: None,
title: None,
annotations: None,
description: Some("c".to_string()),
},
),
]);
let tools = get_openai_tools(&config, Some(tools_map));
// Expect unified_exec first, followed by MCP tools sorted by fully-qualified name.
assert_eq_tool_names(
&tools,
&[
"unified_exec",
"view_image",
"test_server/cool",
"test_server/do",
"test_server/something",
],
);
}
#[test]
fn test_mcp_tool_property_missing_type_defaults_to_string() {
let model_family = find_family_for_model("o3").expect("o3 should be a valid model family");
let config = ToolsConfig::new(&ToolsConfigParams {
model_family: &model_family,
approval_policy: AskForApproval::Never,
sandbox_policy: SandboxPolicy::ReadOnly,
include_plan_tool: false,
include_apply_patch_tool: false,
include_web_search_request: true,
use_streamable_shell_tool: false,
include_view_image_tool: true,
experimental_unified_exec_tool: true,
});
let tools = get_openai_tools(
&config,
Some(HashMap::from([(
"dash/search".to_string(),
mcp_types::Tool {
name: "search".to_string(),
input_schema: ToolInputSchema {
properties: Some(serde_json::json!({
"query": {
"description": "search query"
}
})),
required: None,
r#type: "object".to_string(),
},
output_schema: None,
title: None,
annotations: None,
description: Some("Search docs".to_string()),
},
)])),
);
assert_eq_tool_names(
&tools,
&["unified_exec", "web_search", "view_image", "dash/search"],
);
assert_eq!(
tools[3],
OpenAiTool::Function(ResponsesApiTool {
name: "dash/search".to_string(),
parameters: JsonSchema::Object {
properties: BTreeMap::from([(
"query".to_string(),
JsonSchema::String {
description: Some("search query".to_string())
}
)]),
required: None,
additional_properties: None,
},
description: "Search docs".to_string(),
strict: false,
})
);
}
#[test]
fn test_mcp_tool_integer_normalized_to_number() {
let model_family = find_family_for_model("o3").expect("o3 should be a valid model family");
let config = ToolsConfig::new(&ToolsConfigParams {
model_family: &model_family,
approval_policy: AskForApproval::Never,
sandbox_policy: SandboxPolicy::ReadOnly,
include_plan_tool: false,
include_apply_patch_tool: false,
include_web_search_request: true,
use_streamable_shell_tool: false,
include_view_image_tool: true,
experimental_unified_exec_tool: true,
});
let tools = get_openai_tools(
&config,
Some(HashMap::from([(
"dash/paginate".to_string(),
mcp_types::Tool {
name: "paginate".to_string(),
input_schema: ToolInputSchema {
properties: Some(serde_json::json!({
"page": { "type": "integer" }
})),
required: None,
r#type: "object".to_string(),
},
output_schema: None,
title: None,
annotations: None,
description: Some("Pagination".to_string()),
},
)])),
);
assert_eq_tool_names(
&tools,
&["unified_exec", "web_search", "view_image", "dash/paginate"],
);
assert_eq!(
tools[3],
OpenAiTool::Function(ResponsesApiTool {
name: "dash/paginate".to_string(),
parameters: JsonSchema::Object {
properties: BTreeMap::from([(
"page".to_string(),
JsonSchema::Number { description: None }
)]),
required: None,
additional_properties: None,
},
description: "Pagination".to_string(),
strict: false,
})
);
}
#[test]
fn test_mcp_tool_array_without_items_gets_default_string_items() {
let model_family = find_family_for_model("o3").expect("o3 should be a valid model family");
let config = ToolsConfig::new(&ToolsConfigParams {
model_family: &model_family,
approval_policy: AskForApproval::Never,
sandbox_policy: SandboxPolicy::ReadOnly,
include_plan_tool: false,
include_apply_patch_tool: false,
include_web_search_request: true,
use_streamable_shell_tool: false,
include_view_image_tool: true,
experimental_unified_exec_tool: true,
});
let tools = get_openai_tools(
&config,
Some(HashMap::from([(
"dash/tags".to_string(),
mcp_types::Tool {
name: "tags".to_string(),
input_schema: ToolInputSchema {
properties: Some(serde_json::json!({
"tags": { "type": "array" }
})),
required: None,
r#type: "object".to_string(),
},
output_schema: None,
title: None,
annotations: None,
description: Some("Tags".to_string()),
},
)])),
);
assert_eq_tool_names(
&tools,
&["unified_exec", "web_search", "view_image", "dash/tags"],
);
assert_eq!(
tools[3],
OpenAiTool::Function(ResponsesApiTool {
name: "dash/tags".to_string(),
parameters: JsonSchema::Object {
properties: BTreeMap::from([(
"tags".to_string(),
JsonSchema::Array {
items: Box::new(JsonSchema::String { description: None }),
description: None
}
)]),
required: None,
additional_properties: None,
},
description: "Tags".to_string(),
strict: false,
})
);
}
#[test]
fn test_mcp_tool_anyof_defaults_to_string() {
let model_family = find_family_for_model("o3").expect("o3 should be a valid model family");
let config = ToolsConfig::new(&ToolsConfigParams {
model_family: &model_family,
approval_policy: AskForApproval::Never,
sandbox_policy: SandboxPolicy::ReadOnly,
include_plan_tool: false,
include_apply_patch_tool: false,
include_web_search_request: true,
use_streamable_shell_tool: false,
include_view_image_tool: true,
experimental_unified_exec_tool: true,
});
let tools = get_openai_tools(
&config,
Some(HashMap::from([(
"dash/value".to_string(),
mcp_types::Tool {
name: "value".to_string(),
input_schema: ToolInputSchema {
properties: Some(serde_json::json!({
"value": { "anyOf": [ { "type": "string" }, { "type": "number" } ] }
})),
required: None,
r#type: "object".to_string(),
},
output_schema: None,
title: None,
annotations: None,
description: Some("AnyOf Value".to_string()),
},
)])),
);
assert_eq_tool_names(
&tools,
&["unified_exec", "web_search", "view_image", "dash/value"],
);
assert_eq!(
tools[3],
OpenAiTool::Function(ResponsesApiTool {
name: "dash/value".to_string(),
parameters: JsonSchema::Object {
properties: BTreeMap::from([(
"value".to_string(),
JsonSchema::String { description: None }
)]),
required: None,
additional_properties: None,
},
description: "AnyOf Value".to_string(),
strict: false,
})
);
}
#[test]
fn test_shell_tool_for_sandbox_workspace_write() {
let sandbox_policy = SandboxPolicy::WorkspaceWrite {
writable_roots: vec!["workspace".into()],
network_access: false,
exclude_tmpdir_env_var: false,
exclude_slash_tmp: false,
};
let tool = super::create_shell_tool_for_sandbox(&sandbox_policy);
let OpenAiTool::Function(ResponsesApiTool {
description, name, ..
}) = &tool
else {
panic!("expected function tool");
};
assert_eq!(name, "shell");
let expected = "Runs a shell command and returns its output.";
assert_eq!(description, expected);
}
#[test]
fn test_shell_tool_for_sandbox_readonly() {
let tool = super::create_shell_tool_for_sandbox(&SandboxPolicy::ReadOnly);
let OpenAiTool::Function(ResponsesApiTool {
description, name, ..
}) = &tool
else {
panic!("expected function tool");
};
assert_eq!(name, "shell");
let expected = "Runs a shell command and returns its output.";
assert_eq!(description, expected);
}
#[test]
fn test_shell_tool_for_sandbox_danger_full_access() {
let tool = super::create_shell_tool_for_sandbox(&SandboxPolicy::DangerFullAccess);
let OpenAiTool::Function(ResponsesApiTool {
description, name, ..
}) = &tool
else {
panic!("expected function tool");
};
assert_eq!(name, "shell");
assert_eq!(description, "Runs a shell command and returns its output.");
}
}