update mcp definition example

This commit is contained in:
2026-08-20 09:58:55 +07:00
parent 5829c82d05
commit 7ffb720f86
11 changed files with 346 additions and 918 deletions
+1 -1
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@@ -2,7 +2,7 @@
julia_version = "1.12.6"
manifest_format = "2.0"
project_hash = "aa163e2bf572632825162936e107be18384fd40f"
project_hash = "3ff1783eadf40ccb51801954aa0a8df935689752"
[[deps.Accessors]]
deps = ["CompositionsBase", "ConstructionBase", "Dates", "InverseFunctions", "MacroTools"]
-4
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@@ -12,13 +12,11 @@ Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
GeneralUtils = "c6c72f09-b708-4ac8-ac7c-2084d70108fe"
HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"
JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
LLMMCTS = "d76c5a4d-449e-4835-8cc4-dd86ec44f241"
LibPQ = "194296ae-ab2e-5f79-8cd4-7183a0a5a0d1"
NATS = "55e73f9c-eeeb-467f-b4cc-a633fde63d2a"
PrettyPrinting = "54e16d92-306c-5ea0-a30b-337be88ac337"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
SQLLLM = "2ebc79c7-cc10-4a3a-9665-d2e1d61e63d3"
Serialization = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
URIs = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
@@ -31,7 +29,5 @@ DataFrames = "1.7.0"
GeneralUtils = "0.5.10"
HTTP = "2.4.0"
JSON = "1.6.1"
LLMMCTS = "0.1.5"
NATS = "0.1.0"
SQLLLM = "0.2.8"
msghandler = "1.2.1"
+41 -5
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@@ -1,5 +1,41 @@
check my understand:
1) if LLM didn't use tool calls, assistantMessage get pushed into agent._state.messages and
it will be the latest message in agent._state.messages. then _agentLoop() can pick it as
the output to outputChannel
2) if LLM use tool calls but toolResultBatch.terminate is false, assistantMessageToolCall
# "tools/list" input:
mcpServer("tools/list")
# sending out payload before smart packed by msghandler
Dict(
"method"=> "tools/list"
)
# expected return after smart unpacked by msghandler
Dict("tools" => [
Dict("toolName" => "getWeather",
"title" => "Weather Lookup",
"description" => "Fetch current weather for a city.",
"inputSchema" => Dict("type"=>"object",
"properties" => Dict("city"=>Dict("type"=>"string", "description"=>"City name"),
"units"=>Dict("type"=>"string", "enum"=>["celsius","fahrenheit"], "default"=>"celsius")),
"required" => ["city"])
)
])
# "tools/call" input:
mcpServer("tools/call", "getWeather", Dict("city"=>"Tokyo", "units"=>"celsius"))
# sending out payload before smart packed by msghandler
Dict(
"method"=> "tools/call",
"tools"=> Dict("toolName"=>"getWeather", "arguments"=>Dict("city"=>"Tokyo", "units"=>"celsius"))
)
# expected return after smart unpacked by msghandler
Dict(
"toolName"=>"getWeather",
"content": [{"type": "text", "text": "Weather in Tokyo: Sunny, 22°C"}],
"isError": false
)
# If an error occurs, mcpServer returns after smart unpacked by msghandler:
Dict(
"toolName"=>"getWeather",
"content": [],
"error": Dict("code"=>1, "message"=>"City not found"),
"isError": true
)
+3
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@@ -6,3 +6,6 @@ check my understanding
Is my understanding correct?
the user can provide NATS connection to MCP server by adding agent.mcpserver (a callable struct) for communication with MCP server just like agent.llmCall (also a callable struct). I think communicating with MCP server is just send/receive JSON text right?
Moreover, for simplicity I want to all tools into an MCP server so an agent can be instantiated with only listTools() in tool store then populate tools from MCP server later.
what do you think?
+40 -66
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@@ -1,66 +1,40 @@
module YiemAgent
export register_all_tools
""" Order by dependencies of each file. The 1st included file must not depend on any other
files and each file can only depend on the file included before it.
"""
include("type.jl")
using .type
include("utils.jl")
using .utils
include("tools/getWeather.jl")
include("tools/getTime.jl")
include("tools/searchWine.jl")
include("tools/writeTool.jl")
include("toolRegistry.jl")
using .toolRegistry
function register_all_tools(store::toolRegistry.toolStore)
registerTool(store, getWeatherTool())
registerTool(store, getTimeTool())
registerTool(store, searchWineTool())
registerTool(store, writeToolTool())
registerTool(store, listTool(store))
return store.tools
end
# include("llmfunction.jl")
# using .llmfunction
include("agentCore.jl")
using .agentCore
include("api.jl")
using .api
# ---------------------------------------------- 100 --------------------------------------------- #
end # module YiemAgent_v1
module YiemAgent
export register_all_tools
""" Order by dependencies of each file. The 1st included file must not depend on any other
files and each file can only depend on the file included before it.
"""
include("type.jl")
using .type
include("utils.jl")
using .utils
include("toolRegistry.jl")
using .toolRegistry
function register_all_tools(store::toolRegistry.toolStore, mcpserver=nothing)
# Only register listTools — all other tools come from MCP server at runtime
registerTool(store, listTool(store, mcpserver))
return store.tools
end
# include("llmfunction.jl")
# using .llmfunction
include("agentCore.jl")
using .agentCore
include("api.jl")
using .api
# ---------------------------------------------- 100 --------------------------------------------- #
end # module YiemAgent_v1
+85 -4
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@@ -9,9 +9,9 @@ using JSON, DataStructures, Dates, UUIDs, HTTP, Random, PrettyPrinting, Serializ
using GeneralUtils
using ..type, ..utils, ..toolRegistry
function register_all_tools(store::toolRegistry.toolStore)
function register_all_tools(store::toolRegistry.toolStore, mcpServer=nothing)
# Call parent module's version which has access to tool functions
parentmodule(@__MODULE__).register_all_tools(store)
parentmodule(@__MODULE__).register_all_tools(store, mcpServer)
end
# ---------------------------------------------- 100 --------------------------------------------- #
@@ -49,7 +49,83 @@ mutable struct yiemAgent <: agent # High-level agent wrapper
# Each block has a type — "text", "thinking", or "toolCall".
# The code filters for type === "toolCall" blocks, then passes them to executeToolCalls().
llmCall
# Callable struct for MCP server communication.
# Called as: mcpServer("tools/list") → returns parsed JSON dict of available tools
# mcpServer("tools/call", toolName, arguments) → returns tool result as parsed JSON dict
#
# # Example (weather tool)
# # User provides a callable struct
# struct MyMCPClient
# natsConn::NATS.Connection
# topic::String
# senderID::String
# fileserver_url::String
# end
#
# function (c::MyMCPClient)(method::String)
# payload = Dict("method"=> method)
# payloads = [("method", payload, "dictionary")]
# _, msg_envelope_json_str = msghandler.smartpack(
# c.topic, payloads; sender_id=c.senderID,
# msg_purpose="mcp_tools_list", fileserver_url=c.fileserver_url)
# reply = NATS.request(c.natsConn, c.topic, msg_envelope_json_str, timeout=180)
# incoming_env = msghandler.smartunpack(String(reply.payload))
# return incoming_env["payloads"][1][2]
# end
#
# function (c::MyMCPClient)(method::String, toolName::String, arguments::Dict{String,Any})
# payload = Dict("method"=> method, "toolName"=> toolName, "arguments"=>arguments)
# payloads = [("method", payload, "dictionary"),]
# _, msg_envelope_json_str = msghandler.smartpack(
# c.topic, payloads; sender_id=c.senderID,
# msg_purpose="mcp_tool_call", fileserver_url=c.fileserver_url)
# reply = NATS.request(c.natsConn, c.topic, msg_envelope_json_str, timeout=180)
# incoming_env = msghandler.smartunpack(String(reply.payload))
# return incoming_env["payloads"][1][2]
# end
#
# # "tools/list" input:
# mcpServer("tools/list")
# # sending out payload before smart packed by msghandler:
# Dict("method"=> "tools/list")
# # expected return after smart unpacked by msghandler:
# Dict("tools" => [
# Dict(
# "toolName" => "getWeather",
# "title" => "Weather Lookup",
# "description" => "Fetch current weather for a city.",
# "inputSchema" => Dict("type"=>"object",
# "properties" => Dict("city"=>Dict("type"=>"string", "description"=>"City name"),
# "units"=>Dict("type"=>"string", "enum"=>["celsius","fahrenheit"], "default"=>"celsius")),
# "required" => ["city"])
# )
# ])
#
# # "tools/call" input:
# mcpServer("tools/call", "getWeather", Dict("city"=>"Tokyo", "units"=>"celsius"))
# # sending out payload before smart packed by msghandler:
# Dict(
# "method"=> "tools/call",
# "toolName"=>"getWeather",
# "arguments"=>Dict("city"=>"Tokyo", "units"=>"celsius")
# )
# # expected return after smart unpacked by msghandler (success):
# Dict(
# "toolName"=> "getWeather",
# "content" => [{"type" => "text", "text" => "Weather in Tokyo: Sunny, 22°C"}],
# "error"=> "",
# "isError" => false
# )
# # expected return after smart unpacked by msghandler (error):
# Dict(
# "toolName"=> "getWeather",
# "content" => [],
# "error" => Dict("code"=>1, "message"=>"City not found"),
# "isError" => true
# )
mcpServer
# Callback invoked before executing a tool call (ask for user permission/confirmation/abort, etc..)
beforeToolCall::Union{Function, Nothing}
@@ -86,6 +162,9 @@ on `inputChannel` and `followUpChannel` channels concurrently.
- `maxRetryDelayMs::Union{Int64, Nothing}`: Maximum delay between retries in milliseconds (default: `nothing`)
- `parallelToolExecute::Bool`: Run tool calls in parallel (default: `false`)
- `agentEventSink::Function`: Callback to receive agent events
- `mcpServer`: Callable struct for MCP server communication. Called as
`mcpServer("tools/list")` to discover tools, or `mcpServer("tools/call", args)`
to execute a tool. Returns parsed JSON dicts. (default: `nothing`)
# Returns
- A new `yiemAgent` instance with an active background task
@@ -106,6 +185,7 @@ function yiemAgent(
maxRetryDelayMs::Union{Int64, Nothing}=nothing,
parallelToolExecute::Bool=false,
agentEventSink=agentEventSink,
mcpServer=nothing,
)
# Create channels: input (user -> agent), followUp (async queue), output (agent -> user)
inputChannel = Channel(16)
@@ -114,7 +194,7 @@ function yiemAgent(
# load tools (statically registered at module init)
toolStore1 = toolStore(name="myagent")
register_all_tools(toolStore1)
register_all_tools(toolStore1, mcpServer)
# Create struct with a placeholder task, then spawn and replace it
agent = yiemAgent(
@@ -126,6 +206,7 @@ function yiemAgent(
prepareContext,
formatMsgForLLM,
llmCall,
mcpServer,
beforeToolCall,
afterToolCall,
# prepareNextTurn,
+176 -34
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@@ -7,7 +7,7 @@ using JSON, DataStructures
using ..type
"""
Per-agent isolated tool storage.
Per-agent isolated tool storage.
Each agent gets its own `toolStore` so tool registration is independent —
`registerTool(store, tool)` only affects that agent's tool set.
@@ -39,61 +39,203 @@ function toolStore(; name::String="default")::toolStore
toolStore(OrderedDict{String, agentTool}(), name)
end
# ── MCP helper functions ────────────────────────────────────────────
"""
listTool(store::toolStore) -> agentTool
Extract text from MCP tool result content array.
Return an `agentTool` definition for listing registered tools.
Handles MCP's content format: [{"type":"text","text":"..."}]
"""
function _extract_text_content(result::Dict)::String
content = get(result, "content", Any[])
if content isa Vector && !isempty(content)
lines = String[]
for block in content
if block isa Dict && get(block, "type", "") == "text"
push!(lines, string(get(block, "text", "")))
end
end
if !isempty(lines)
return join(lines, "\n")
end
end
return JSON.json(result)
end
Each call produces a **new** tool object that captures (closes over)
`store`. `register_all_tools` auto-registers one so the LLM can discover tools
at runtime.
"""
Wrap an MCP tool definition as an `agentTool`.
The returned tool's `execute` function calls the MCP server's "tools/call"
method with the validated arguments.
"""
function _wrap_mcp_tool(mcpserver, tool_def::Dict{String,Any})::agentTool
name = tool_def["toolName"]
title = get(tool_def, "title", name)
desc = get(tool_def, "description", "")
input_schema = get(tool_def, "inputSchema", Dict{String,Any}())
# Normalize inputSchema to OpenAI function format
if haskey(input_schema, "properties") && input_schema["type"] == "object"
params = Dict(
"type" => "object",
"properties" => input_schema["properties"],
"required" => get(input_schema, "required", Any[]),
)
else
params = Dict(
"type" => "object",
"properties" => Dict{String,Any}(),
"required" => Any[],
)
end
return agentTool(
name=name,
label=title,
description=desc,
inputSchema=params,
execute=(toolCallId::String, args::Dict{String,Any},
signal::Union{Nothing,abortSignal},
onPartialResult::Function,
llmCall=nothing) -> begin
try
response = mcpserver("tools/call", name, args)
result_data = get(response, "result", response)
content_text = _extract_text_content(result_data)
is_error = get(result_data, "isError", false)
return agentToolResult(
[textContent(content_text)],
Dict{Any,Any}("isError" => is_error),
nothing, false
)
catch e
errMsg = sprint(showerror, e)
return agentToolResult(
[textContent("MCP call error: $errMsg")],
Dict{Any,Any}("error" => errMsg),
nothing, false
)
end
end,
prepareArguments=nothing,
validateRequiredArgs=nothing,
parallelToolExecute=false,
)
end
"""
Discover and register MCP tools into `store.tools`.
Queries the MCP server via `mcpserver("tools/list")`, parses the response,
and registers each discovered tool. Skips tools already registered.
Returns `(new_count, tool_list_text)`.
"""
function _register_mcp_tools(mcpserver, store::toolStore)::Tuple{Int, String}
if mcpserver === nothing
return (0, "")
end
try
response = mcpserver("tools/list")
tools_array = response["tools"]
new_count = 0
for tool_def in tools_array
name = tool_def["toolName"]
if haskey(store.tools, name)
continue
end
wrapped = _wrap_mcp_tool(mcpserver, tool_def)
store.tools[name] = wrapped
new_count += 1
end
# Build readable tool list
lines = String[
"- $(t.name): $(t.label)$(t.description)"
for (k, t) in store.tools
]
tool_list_text = "Discovered $(new_count) MCP tools. Total registered: $(length(store.tools)).\nAvailable tools:\n" * join(lines, "\n")
return (new_count, tool_list_text)
catch e
errMsg = sprint(showerror, e)
return (0, "MCP tools/list failed: $errMsg")
end
end
"""
listTool(store::toolStore, mcpserver) -> agentTool
MCP-aware listTools tool.
First call: queries the MCP server via `mcpserver("tools/list")`, registers
all discovered tools into the shared `store.tools` (in-place mutation),
then returns the full tool list.
Subsequent calls: returns the current list (tools remain registered).
This is the only pre-registered tool. All other tools come from the
MCP server and are loaded at runtime when the LLM calls listTools().
# Arguments
- `store`: The tool store whose tools will be listed when the tool runs
- `store`: The tool store to populate with MCP tools
- `mcpserver`: A callable struct that communicates with the MCP server.
Called as `mcpserver("tools/list")` or `mcpserver("tools/call", args)`.
Returns parsed JSON dicts.
# Example
```julia
julia> store = toolStore(name="agent1");
# User provides an MCP server client (callable struct)
mcp = MyMCPClient("nats://localhost:4222")
store = toolStore(name="agent1")
registerTool(store, listTool(store, mcp))
julia> register_all_tools(store) # auto-registers listTools
[toolRegistry:agent1] Loaded tool: getWeather (Weather Lookup)
[toolRegistry:agent1] Registered tool: listTools
julia> tools = getTools(store)
OrderedDict{String, agentTool} with 4 entries:
"getWeather" => agentTool(...)
"getTime" => agentTool(...)
"writeTool" => agentTool(...)
"listTools" => agentTool(...)
# When agent calls listTools(), tools are discovered from MCP server
# and registered into store.tools in real time.
```
"""
function listTool(store::toolStore)::agentTool
function listTool(store::toolStore, mcpserver)::agentTool
return agentTool(
name = "listTools",
label = "List Tools",
description = "List all available tools with their names, labels, and descriptions. Use this before creating a new tool to check for name collisions.",
inputSchema = Dict{String,Any}(
name="listTools",
label="List Tools",
description="List all available tools. First call discovers and registers all tools from the MCP server. After discovery, new tools become immediately available for use.",
inputSchema=Dict{String,Any}(
"type" => "object",
"properties" => Dict{String,Any}(),
"required" => Any[]
),
execute = (toolCallId, args, signal, onPartialResult) -> begin
tools = getTools(store)
if isempty(tools)
result_text = "No tools registered."
execute=(toolCallId::String, args::Dict{String,Any},
signal::Union{Nothing,abortSignal},
onPartialResult::Function, llmCall=nothing) -> begin
# Discover and register MCP tools (idempotent — skips already registered)
new_count, tool_list = _register_mcp_tools(mcpserver, store)
# Always include listTools itself in the count
total = length(store.tools)
if new_count > 0
result_text = tool_list
else
lines = String["- $(t.name): $(t.label)$(t.description)" for (k, t) in tools]
result_text = "Available tools:\n" * join(lines, "\n")
# Already discovered — just return current list
lines = String[
"- $(t.name): $(t.label)$(t.description)"
for (k, t) in store.tools
]
result_text = "Available tools ($total):\n" * join(lines, "\n")
end
return agentToolResult(
[textContent(result_text)],
Dict{Any,Any}("count" => length(tools)),
Dict{Any,Any}("count" => total),
nothing, false
)
end,
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = false
prepareArguments=nothing,
validateRequiredArgs=nothing,
parallelToolExecute=false,
)
end
@@ -115,7 +257,7 @@ Add `tool` to `store`, overwriting any existing tool with the same name.
```julia
julia> store = toolStore(name="agent1");
julia> registerTool(store, listTool(store))
julia> registerTool(store, listTool(store, nothing))
[toolRegistry:agent1] Registered tool: listTools
OrderedDict{String, agentTool} with 1 entry:
"listTools" => agentTool(...)
-83
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@@ -1,83 +0,0 @@
using .type
using Dates
"""
Validate required arguments for the getTime tool.
Demonstrates custom validation beyond simple required-field checking:
- Ensures at least one time source (timezone or city) is provided
- Validates timezone is in IANA format if specified
- Validates city name is not empty if specified
# Arguments
- `args::Dict{String,Any}`: Arguments from the LLM
# Returns
- `nothing` if validation passes
- `String` error message if validation fails
"""
function getTimeValidateRequiredArgs(args::Dict{String,Any})::Union{Nothing,String}
tz = get(args, "timezone", nothing)
city = get(args, "city", "")
hasTz = tz !== nothing && !isempty(tz)
hasCity = !isempty(city)
# At least one of timezone or city is required
if !hasTz && !hasCity
return "Missing required argument: provide at least one of 'timezone' or 'city'"
end
# Validate timezone format (IANA tz database: "Continent/City" or "Continent/City/SubCity")
if hasTz
tz_str = string(tz)
if !occursin(r"^[A-Za-z]+\/[A-Za-z]+(/[A-Za-z]+)*$", tz_str)
return "Invalid timezone format: '$tz_str'. Use IANA format, e.g. 'America/New_York' or 'Asia/Tokyo'"
end
end
return nothing
end
"""
Execute the getTime tool.
Returns mock time data for the given timezone or city.
"""
function getTimeExecute(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal},
onPartialResult, llmCall=nothing)
tz = get(args, "timezone", nothing)
city = get(args, "city", "")
if tz !== nothing
result = "Current time in $(tz): $(now())"
else
result = "Current time in $(city): $(now())"
end
return agentToolResult(
[textContent(result)],
Dict{Any,Any}(), nothing, false
)
end
"""
Define and return the getTime agentTool.
"""
function getTimeTool()::agentTool
return agentTool(
name = "getTime",
label = "Time Lookup",
description = "Get current local time for a timezone or city.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"timezone" => Dict("type" => "string", "description" => "IANA timezone, e.g. 'America/New_York'"),
"city" => Dict("type" => "string", "description" => "City name as fallback")
),
"required" => []
),
execute = getTimeExecute,
prepareArguments = nothing,
validateRequiredArgs = getTimeValidateRequiredArgs,
parallelToolExecute = false
)
end
-48
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@@ -1,48 +0,0 @@
using msghandler
using .type
"""
Execute the getWeather tool.
Returns mock weather data for the given city and temperature units.
"""
function getWeatherExecute(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal},
agentEventSink, llmCall=nothing)
agentEventSink("Getting weather...")
city = get(args, "city", "")
units = get(args, "units", "celsius")
temp = units == "fahrenheit" ? "72" : "22"
unit_symbol = units == "celsius" ? "°C" : "°F"
return agentToolResult(
[textContent("Weather in $(city): Sunny, $(temp)$(unit_symbol)")],
Dict{Any,Any}(),
nothing,
false
)
end
"""
Define and return the getWeather agentTool.
"""
function getWeatherTool()::agentTool
return agentTool(
name = "getWeather",
label = "Weather Lookup",
description = "Fetch current weather and forecast for a given city.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"city" => Dict("type" => "string", "description" => "City and country, e.g., 'San Francisco, CA' or 'Tokyo, Japan'"),
"units" => Dict("type" => "string", "enum" => ["celsius", "fahrenheit"], "default" => "celsius", "description" => "Temperature scale")
),
"required" => ["city"]
),
execute = getWeatherExecute,
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = false
)
end
-397
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@@ -1,397 +0,0 @@
using .type
using LibPQ, DataFrames, JSON, DataStructures
using Dates, Random, HTTP
using GeneralUtils
# ── Database config — update for your environment ───────────────────────
const DB_CONFIG = Dict{String,Any}(
"host" => "localhost",
"port" => 5432,
"dbname" => "winedb",
"user" => "postgres",
"password" => "",
)
"""
Execute the search_wine_database! tool.
Uses the agent's LLM to generate SQL from the free-form text query,
then executes it against the wine database and returns formatted results.
"""
function searchWineExecute(
toolCallId::String,
args::Dict{String,Any},
signal::Union{Nothing,abortSignal},
agentEventSink,
llmCall,
)::agentToolResult
#WORKING
search_query = get(args, "searchQuery", "")::String
if isempty(search_query)
return agentToolResult(
[textContent("Please provide a search query for the wine database.")],
Dict{Any,Any}(), nothing, false
)
end
agentEventSink("searchWineExecute: query=$search_query")
# ── SQL generation prompt ───────────────────────────────────────────
systemmsg = """
# database_search_guidelines
- Keep SQL queries focused only on the provided information.
- Use wildcard character (%) to search more effectively.
- Do not create any table in the database.
- Text information in the database is usually stored in lower case.
If your search returns empty, try using lower case to search.
- Overly strict conditions usually yield empty results.
- Use ILIKE for case-insensitive text matching.
- Only output the SQL query — do not wrap it in backticks or add comments.
# situation
You are a wine store database assistant. You will be given a user's
natural language search query and the database table schema.
# objective
Generate a single SQL query to find wines matching the user's request.
# your responsibility includes
Fulfill the objective.
# you should respond with ONLY the SQL query string, ending with ';'
"""
table_schema = """
CREATE TABLE wine (
wine_id uuid primary key default gen_random_uuid (),
wine_name varchar(128) not null,
winery varchar(128) not null,
vintage integer not null,
region varchar(128) not null,
country varchar(128) not null,
wine_type varchar(128) not null,
grape varchar(128) not null,
serving_temperature varchar(128) not null,
intensity integer,
sweetness integer,
tannin integer,
acidity integer,
fizziness integer,
tasting_notes text,
image_url jsonb,
manufacturer_sku text,
note text,
other_attributes jsonb,
created_time timestamptz default current_timestamp,
updated_time timestamptz default current_timestamp,
description text
);
CREATE TABLE retailer (
retailer_id uuid primary key default gen_random_uuid (),
retailer_name varchar(128) not null,
retailer_username varchar(128) not null,
retailer_password varchar(128) not null,
retailer_address text not null,
country varchar(128) not null,
contact_person varchar(128) not null,
telephone varchar(128) not null,
email varchar(128) not null,
note text,
other_attributes jsonb,
created_time timestamptz default current_timestamp,
updated_time timestamptz default current_timestamp,
description text
);
CREATE TABLE retailer_wine (
retailer_id uuid references retailer(retailer_id),
wine_id uuid references wine(wine_id),
constraint retailer_wine_id primary key (retailer_id, wine_id),
price NUMERIC(10, 2),
currency varchar(3) not null,
created_time timestamptz default current_timestamp,
updated_time timestamptz default current_timestamp
);
"""
context = "<internal_context_for_assistant>\n<database_table_schema>\n$table_schema\n</database_table_schema>\n</internal_context_for_assistant>\n\n"
input = context * "User query: $search_query\n\nGenerate the SQL query:"
# ── Call LLM for SQL generation ────────────────────────────────────
max_attempts = 5
generated_sql = nothing
for attempt in 1:max_attempts
msg = Dict(
"messages" => [
Dict(
"role" => "system",
"content" => [Dict("type" => "text", "text" => systemmsg)],
),
Dict(
"role" => "user",
"content" => [Dict("type" => "text", "text" => input)],
),
],
"temperature" => 0.7,
)
llm_response = llmCall(msg)
# Clean the response — extract SQL from potential markdown/code blocks
sql_text = _clean_sql_response(llm_response)
# Validate it looks like SQL
if _is_valid_sql(sql_text)
generated_sql = sql_text
agentEventSink("searchWine: generated SQL (attempt $attempt)\n$sql_text")
break
else
agentEventSink("searchWine: invalid SQL attempt $attempt: $sql_text")
end
end
if generated_sql === nothing
return agentToolResult(
[textContent("Failed to generate a valid SQL query for your search. Please try rephrasing.")],
Dict{Any,Any}("error" => "sql_generation_failed"), nothing, false
)
end
# ── Execute SQL ────────────────────────────────────────────────────
try
conn = LibPQ.Connection(DB_CONFIG)
# Ensure LIMIT to prevent large result sets
sanitized_sql = _ensure_limit(generated_sql)
agentEventSink("searchWine: executing\n$sanitized_sql")
result = LibPQ.execute(conn, sanitized_sql)
close(conn)
if !LibPQ.hasdata(result)
return agentToolResult(
[textContent("No wines found matching your search. Try loosening your criteria.")],
Dict{Any,Any}("count" => 0), nothing, false
)
end
df = DataFrame(result)
num_rows, num_cols = size(df)
if num_cols > 30
return agentToolResult(
[textContent("The result has more than 30 columns. Please be more specific in your search.")],
Dict{Any,Any}("error" => "too_many_columns"), nothing, false
)
end
# Randomly sample up to 2 rows for display if more than 2 results
display_df = df
if num_rows > 2
idx = sample(1:num_rows, min(2, num_rows), replace=false)
display_df = df[idx, :]
end
# Convert to vector of dicts
result_vec = GeneralUtils.dfToVectorDict(display_df)
# Fetch bottle images if available
for d in result_vec
image_url_json_str = get(d, "image_url", nothing)
if image_url_json_str !== nothing && !isempty(string(image_url_json_str))
try
image_url_json_obj = JSON.parse(string(image_url_json_str))
base_url = "http://192.168.88.106:8080/"
if haskey(image_url_json_obj, "bottle")
url = base_url * string(image_url_json_obj["bottle"])
image_data = HTTP.get(url)
image_base64_string = base64encode(image_data.body)
d["image"] = image_base64_string
end
catch
# Skip image fetch on error
end
end
end
# Format results as readable text
result_str = _format_wine_results(display_df)
return agentToolResult(
[textContent(result_str)],
Dict{Any,Any}(
"count" => num_rows,
"displayed" => size(display_df, 1),
),
nothing, false
)
catch e
errMsg = sprint(showerror, e)
return agentToolResult(
[textContent("Database error: $errMsg")],
Dict{Any,Any}("error" => errMsg), nothing, false
)
end
end
"""
Extract a SQL query string from the LLM response, handling potential
markdown code blocks, extra text, or JSON wrapping.
"""
function _clean_sql_response(response)::String
text = string(response)
# Try to extract from code block
if occursin("```", text)
extracted = GeneralUtils.extract_triple_backtick_text(text)
if !isempty(extracted)
text = extracted[1]
# Remove "sql\n" prefix if present
if startswith(text, "sql\n") || startswith(text, "SQL\n")
text = text[5:end]
end
end
end
# Remove JSON wrapping if present
text = strip(text)
if startswith(text, "{") && occursin("action_input", text)
# Parse as JSON and extract action_input
try
parsed = JSON.parse(text)
if parsed isa Dict
text = get(parsed, "action_input", text)
end
catch
# Keep original
end
end
# Extract SQL keywords to find the actual query
lines = split(strip(text), '\n')
sql_lines = String[]
for line in lines
stripped = strip(line)
if occursin(r"(?i)(SELECT|FROM|WHERE|JOIN|ORDER|LIMIT|INSERT|UPDATE|DELETE|CREATE|ALTER|DROP|WITH)", stripped)
# Take everything from this line to the end
push!(sql_lines, line)
elseif !isempty(sql_lines)
# Continue collecting if we already found SQL
push!(sql_lines, line)
end
end
result = join(sql_lines, "\n")
# Ensure it ends with semicolon
result = strip(result)
if !endswith(result, ";")
result *= ";"
end
return result
end
"""
Check if a string looks like a valid SQL query.
"""
function _is_valid_sql(sql::String)::Bool
sql = strip(sql)
# Must start with a SQL keyword
has_sql_keyword = occursin(r"(?i)(SELECT|INSERT|UPDATE|DELETE|CREATE|ALTER|DROP|WITH)\s", sql) ||
occursin(r"(?i)(SELECT|INSERT|UPDATE|DELETE|CREATE|ALTER|DROP|WITH)\s*;", sql)
# Must end with semicolon
has_semicolon = endswith(sql, ";")
# Must not be too short (reject single words)
reasonable_length = length(sql) > 10
return has_sql_keyword && has_semicolon && reasonable_length
end
"""
Ensure the SQL query has a LIMIT clause to prevent loading excessive data.
"""
function _ensure_limit(sql::String)::String
sql = strip(sql)
if !occursin(r"(?i)LIMIT", sql)
# Remove existing semicolon, add LIMIT, re-add semicolon
if endswith(sql, ";")
sql = sql[1:end-1]
end
sql *= " ORDER BY RANDOM() LIMIT 2;"
end
return sql
end
"""
Format wine database results as human-readable text.
"""
function _format_wine_results(df::DataFrame)::String
lines = String[]
num_rows = size(df, 1)
for i in 1:num_rows
row = df[i, :]
push!(lines, "$(i). $(get(row, :wine_name, "Unknown")) $(get(row, :vintage, ""))")
winery = get(row, :winery, "Unknown")
region = get(row, :region, "Unknown")
country = get(row, :country, "Unknown")
push!(lines, " Winery: $winery")
push!(lines, " Region: $region, $country")
grape = get(row, :grape, "Unknown")
wtype = get(row, :wine_type, "Unknown")
push!(lines, " Grape: $grape")
push!(lines, " Type: $wtype")
sweetness = get(row, :sweetness, "N/A")
intensity = get(row, :intensity, "N/A")
tannin_val = get(row, :tannin, "N/A")
acidity = get(row, :acidity, "N/A")
push!(lines, " Profile: Sweetness: $sweetness, Intensity: $intensity, Tannin: $tannin_val, Acidity: $acidity")
tasting = get(row, :tasting_notes, nothing)
if tasting !== nothing && !isempty(string(tasting))
tn = string(tasting)
limit = min(200, length(tn))
push!(lines, " Notes: $(tn[1:limit])$(length(tn) > limit ? "..." : "")")
end
price = get(row, :price, "N/A")
currency = get(row, :currency, "")
retailer = get(row, :retailer_name, "N/A")
push!(lines, " Price: $price $currency at $retailer")
push!(lines, "")
end
return join(lines, "\n")
end
"""
Define and return the searchWine agentTool.
"""
function searchWineTool()::agentTool
return agentTool(
name = "searchWine",
label = "Search Wine Database",
description = "Search the wine database for wines matching a free-text query. Uses the LLM to generate SQL and execute it against the database. Returns wine details including name, winery, vintage, tasting notes, and price.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"searchQuery" => Dict(
"type" => "string",
"description" => "Free-text description of the wine you're looking for, e.g., 'a light-bodied red wine from France under 50 dollars'",
),
),
"required" => ["searchQuery"],
),
execute = searchWineExecute,
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = false,
)
end
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@@ -1,276 +0,0 @@
using .type
using JSON
"""
Tool that writes new Julia tool module files to disk.
The agent can use this tool when it encounters a task that no existing tool
can handle. Provide the tool's name, label, description, inputSchema, and
execute logic as Julia code. The tool is written to `src/tools/<name>.jl`.
After calling this tool, add the new file to `YiemAgent.jl` with an `include()`
statement (after `include("toolRegistry.jl")`), then restart the agent.
The new tool must be registered in `register_all_tools()` in `toolRegistry.jl`.
# Example
1. Agent calls writeTool with a spec for a "searchWine" tool
2. writeTool generates src/tools/searchWine.jl
3. Developer adds `include("tools/searchWine.jl")` to YiemAgent.jl
4. Developer adds `registerTool(store, searchWineTool())` to register_all_tools()
5. Restart agent — new tool is available
# How It Works
writeTool is a **file writer**, not a code generator. The LLM provides the
tool logic as `executeCode`, and writeTool wraps it in Julia boilerplate:
- Converts `inputSchema` Dict into Julia `Dict{String,Any}(...)` string
- Indents `executeCode` with 4 spaces
- Wraps it inside `function executeTool(...)::agentToolResult ... end`
- Appends `writeToolTool()` returning an `agentTool` struct
- Writes the combined string to `src/tools/<name>.jl`
# Important Notes
- The `executeCode` string is embedded literally into the generated tool.
Use `args["param_name"]` to access input parameters.
- The code string should be the function body (NOT wrapped in a function).
Lines will be indented with 4 spaces inside the execute function.
- Tool names must be valid Julia identifiers (lowercase letters, digits, underscores,
no leading digits or special characters).
"""
"""
Validate that a tool name is a valid Julia identifier.
"""
function validateToolName(name::String)::Union{Nothing,String}
if !occursin(r"^[a-zA-Z_][a-zA-Z0-9_!]*$", name)
return "Invalid tool name: '$name'. Tool names must be valid Julia identifiers (letters, digits, underscores, starting with a letter or underscore)."
end
return nothing
end
"""
Indent a multi-line code string by the specified number of spaces.
"""
function indent_code(code::String, n::Int)::String
prefix = " "^n
lines = split(code, '\n')
result_lines = String[prefix * line for line in lines]
return join(result_lines, "\n")
end
"""
Convert a Julia Dict to a valid Julia Dict{String,Any}(...) literal string.
"""
function dict_to_julia_literal(d)::String
if d isa Dict
items = String[]
for (k, v) in d
key_str = json_string(k)
val_str = value_to_julia(v)
push!(items, "$key_str => $val_str")
end
return "Dict{String,Any}(" * join(items, ", ") * ")"
else
return value_to_julia(d)
end
end
function value_to_julia(v)::String
if v isa Dict
return dict_to_julia_literal(v)
elseif v isa Vector
items = [value_to_julia(x) for x in v]
return "[" * join(items, ", ") * "]"
elseif v isa String
escaped = replace(v, "\\" => "\\\\")
escaped = replace(escaped, "\"" => "\\\"")
return "\"$escaped\""
elseif v isa Number
return string(v)
elseif v isa Bool
return string(v)
elseif v === nothing
return "nothing"
else
return "\"$(v)\""
end
end
"""
Convert any Julia value to a JSON string.
"""
function json_string(v)::String
return JSON.json(v)
end
"""
Define and return the writeTool agentTool.
"""
function writeToolTool()::agentTool
return agentTool(
name = "writeTool",
label = "Create Tool",
description = "Write a new Julia tool module file to src/tools/<name>.jl. The LLM provides the tool logic as executeCode; writeTool wraps it in Julia boilerplate and writes the file. Restart the agent to load the new tool.",
inputSchema = Dict{String,Any}(
"type" => "object",
"properties" => Dict(
"name" => Dict("type" => "string", "description" => "Unique tool name (valid Julia identifier, no spaces or special chars)"),
"label" => Dict("type" => "string", "description" => "Human-readable tool name shown in tool descriptions"),
"description" => Dict("type" => "string", "description" => "What the tool does (shown to LLM for tool selection decisions)"),
"inputSchema" => Dict(
"type" => "object",
"description" => "JSON Schema describing tool parameters in MCP format"
),
"executeCode" => Dict("type" => "string", "description" => "Julia code for the execute function body. Use args[\"key\"] to access parameters. Do NOT wrap in a function definition."),
"validateCode" => Dict("type" => "string", "optional" => true, "description" => "Optional custom validation Julia code (runs before execute). Use args[\"key\"] to access parameters. Return nothing to pass, or a string error message to fail."),
"prepareCode" => Dict("type" => "string", "optional" => true, "description" => "Optional argument preparation code (runs before validation). Return modified args dict."),
"parallel" => Dict("type" => "boolean", "default" => false, "description" => "Whether this tool can run in parallel with other tools")
),
"required" => ["name", "label", "description", "inputSchema", "executeCode"]
),
execute = (toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult, llmCall=nothing) -> begin
tool_name = get(args, "name", "")::String
tool_label = get(args, "label", tool_name)::String
tool_description = get(args, "description", "")::String
tool_schema = get(args, "inputSchema", Dict{String,Any}())::Dict{String,Any}
execute_code = get(args, "executeCode", "")::String
validate_code = get(args, "validateCode", nothing)::Union{String,Nothing}
prepare_code = get(args, "prepareCode", nothing)::Union{String,Nothing}
parallel = get(args, "parallel", false)::Bool
# Validate tool name
name_err = validateToolName(tool_name)
if name_err !== nothing
return agentToolResult(
[textContent(name_err)],
Dict{Any,Any}(), nothing, false
)
end
# Validate required fields
if isempty(tool_name)
return agentToolResult(
[textContent("Missing required field: 'name'")],
Dict{Any,Any}(), nothing, false
)
end
if isempty(tool_description)
return agentToolResult(
[textContent("Missing required field: 'description'")],
Dict{Any,Any}(), nothing, false
)
end
if isempty(execute_code)
return agentToolResult(
[textContent("Missing required field: 'executeCode'")],
Dict{Any,Any}(), nothing, false
)
end
onPartialResult(Dict("status" => "Generating tool: $tool_name"))
# Build the tool file path
script_dir = dirname(@__FILE__)
tools_dir = dirname(script_dir)
filepath = joinpath(tools_dir, "$(tool_name).jl")
# Check for naming conflicts
if isfile(filepath)
return agentToolResult(
[textContent("Tool file already exists: $filepath. Rename the tool or delete the existing file first.")],
Dict{Any,Any}(), nothing, false
)
end
onPartialResult(Dict("status" => "Writing file: $(basename(filepath))"))
# Convert schema Dict to a Julia Dict literal string
schema_literal = dict_to_julia_literal(tool_schema)
# Build optional validation function
validate_section = if validate_code !== nothing && !isempty(validate_code)
indented = indent_code(validate_code, 4)
"function validateRequiredArgs(args::Dict{String,Any})::Union{Nothing,String}\n$indented\n return nothing\nend\n"
else
""
end
# Build optional prepare function
prepare_section = if prepare_code !== nothing && !isempty(prepare_code)
indented = indent_code(prepare_code, 4)
"function prepareArguments(args::Dict{String,Any})::Dict{String,Any}\n$indented\n return args\nend\n"
else
""
end
# Indent user's execute code for embedding inside execute function body
indented_exec = indent_code(execute_code, 4)
# Escape description for Julia string literal
escaped_desc = replace(tool_description, "\\" => "\\\\")
escaped_desc = replace(escaped_desc, "\"" => "\\\"")
# Build the complete tool file content
parts = String[]
push!(parts, "# Auto-generated tool: $tool_name\n")
push!(parts, "# Generated by writeTool at $(now())\n\n")
if !isempty(validate_section)
push!(parts, validate_section)
push!(parts, "\n")
end
if !isempty(prepare_section)
push!(parts, prepare_section)
push!(parts, "\n")
end
push!(parts, "\n")
push!(parts, "# Execute function\n")
push!(parts, "function executeTool(toolCallId::String, args::Dict{String,Any}, signal::Union{Nothing,abortSignal}, onPartialResult::Function)::agentToolResult\n")
push!(parts, "$indented_exec\n")
push!(parts, "end\n\n")
push!(parts, "# Tool definition\n")
push!(parts, "function getTool()::agentTool\n")
push!(parts, " return agentTool(\n")
push!(parts, " name = \"$(tool_name)\",\n")
push!(parts, " label = \"$(tool_label)\",\n")
push!(parts, " description = \"$(escaped_desc)\",\n")
push!(parts, " inputSchema = $schema_literal,\n")
push!(parts, " execute = executeTool,\n")
if validate_code !== nothing && !isempty(validate_code)
push!(parts, " validateRequiredArgs = validateRequiredArgs,\n")
else
push!(parts, " validateRequiredArgs = nothing,\n")
end
if prepare_code !== nothing && !isempty(prepare_code)
push!(parts, " prepareArguments = prepareArguments,\n")
else
push!(parts, " prepareArguments = nothing,\n")
end
push!(parts, " parallelToolExecute = $parallel\n")
push!(parts, " )\n")
push!(parts, "end\n")
tool_code = join(parts)
# Write the file — tool must be included in YiemAgent.jl and registered in register_all_tools()
write(filepath, tool_code)
onPartialResult(Dict("status" => "Done"))
return agentToolResult(
[textContent("Tool '$(tool_name)' written to $filepath. Add include(\"tools/$(tool_name).jl\") to YiemAgent.jl and registerTool(store, $(tool_name)Tool()) to register_all_tools(), then restart the agent.")],
Dict{Any,Any}(
"file" => filepath,
"name" => tool_name,
"label" => tool_label,
"description" => tool_description,
),
nothing, false
)
end,
prepareArguments = nothing,
validateRequiredArgs = nothing,
parallelToolExecute = false
)
end