Files
ragflow/internal/agent/component/agent_artifact_test.go
euvre 8b065d3ddd fix(agent): collect CodeExec artifacts from ReAct tool responses (#16609)
### Summary

The Go backend Agent component was not returning artifacts produced by
the CodeExec tool. While the Python agent collects the "`_ARTIFACTS`"
envelope from tool responses and appends artifact markdown to the final
content, the Go agent only returned the assistant text, so generated
images were missing from the chat output.

### Changes

- Wire `react.WithMessageFuture()` in `runEinoReActAgent` and store the
resulting `MessageFuture` in the invocation context.
- After the ReAct loop finishes, drain the future and extract
``_ARTIFACTS`` entries from every tool response message.
- Support reading the tool payload from both `msg.Content` and
`msg.UserInputMultiContent` to match eino's tool contract.
- De-duplicate artifacts by URL and render images as `!` and other files
as download links.
- Add `agent_artifact_test.go` with a regression test that simulates a
CodeExec-style tool response carrying an image artifact and verifies it
is collected and formatted.

### Verification

- `go test ./internal/agent/component/... -run
TestAgent_ReActAgent_CollectsArtifactsFromCodeExecTool` passes.
- `go test ./internal/agent/component/... -count=1` compiles; the only
failure is an unrelated DNS-pinning timeout test
(`TestInvoke_ProxyDNSPin`).
- `gofmt` clean for modified files.

### Related

Fixes the behavior shown in the screenshot where the Go agent ignored
the CodeExec-generated PNG artifact.
2026-07-05 20:53:43 +08:00

250 lines
6.7 KiB
Go

package component
import (
"context"
"encoding/json"
"strings"
"testing"
"github.com/cloudwego/eino/components/model"
"github.com/cloudwego/eino/components/tool"
"github.com/cloudwego/eino/compose"
"github.com/cloudwego/eino/flow/agent/react"
"github.com/cloudwego/eino/schema"
)
// artifactTool is an invokable tool that returns a JSON envelope with _ARTIFACTS.
type artifactTool struct {
result string
}
func (t *artifactTool) Info(_ context.Context) (*schema.ToolInfo, error) {
return &schema.ToolInfo{
Name: "artifact_tool",
Desc: "returns artifacts",
ParamsOneOf: schema.NewParamsOneOfByParams(map[string]*schema.ParameterInfo{
"unused": {Type: schema.String},
}),
}, nil
}
func (t *artifactTool) InvokableRun(_ context.Context, _ string, _ ...tool.Option) (string, error) {
return t.result, nil
}
// artifactModel is a scripted ToolCallingChatModel that emits one tool call
// and then a final answer.
type artifactModel struct {
turn int
callID string
toolName string
toolArgs string
final string
}
func (m *artifactModel) Generate(_ context.Context, _ []*schema.Message, _ ...model.Option) (*schema.Message, error) {
m.turn++
if m.turn == 1 {
return &schema.Message{
Role: schema.Assistant,
ToolCalls: []schema.ToolCall{{
ID: m.callID,
Type: "function",
Function: schema.FunctionCall{
Name: m.toolName,
Arguments: m.toolArgs,
},
}},
}, nil
}
return &schema.Message{Role: schema.Assistant, Content: m.final}, nil
}
func (m *artifactModel) Stream(_ context.Context, _ []*schema.Message, _ ...model.Option) (*schema.StreamReader[*schema.Message], error) {
sr, sw := schema.Pipe[*schema.Message](1)
sw.Close()
return sr, nil
}
func (m *artifactModel) WithTools(tools []*schema.ToolInfo) (model.ToolCallingChatModel, error) {
return m, nil
}
func TestAgent_ReActAgent_CollectsArtifactsFromCodeExecTool(t *testing.T) {
toolResult, err := json.Marshal(map[string]any{
"tool_called": true,
"message": "CodeExec executed",
"_ARTIFACTS": []map[string]any{
{
"name": "agent_artifact_bug_demo.png",
"url": "/api/v1/documents/artifact/1ae8d553478544628bb8be267d502371.png",
},
},
})
if err != nil {
t.Fatalf("marshal tool result: %v", err)
}
opt, future := react.WithMessageFuture()
agent, err := react.NewAgent(context.Background(), &react.AgentConfig{
ToolCallingModel: &artifactModel{
callID: "call_1",
toolName: "artifact_tool",
toolArgs: `{"unused":"x"}`,
final: "The image has been generated.",
},
ToolsConfig: compose.ToolsNodeConfig{
Tools: []tool.BaseTool{&artifactTool{result: string(toolResult)}},
},
MaxStep: 3,
})
if err != nil {
t.Fatalf("react.NewAgent: %v", err)
}
_, err = agent.Generate(context.Background(), []*schema.Message{
schema.UserMessage("generate a test image"),
}, opt)
if err != nil {
t.Fatalf("agent.Generate: %v", err)
}
// Drain the future so collectArtifactsFromToolCalls can iterate synchronously.
msgs := drainFutureMessages(t, future)
if len(msgs) == 0 {
t.Fatal("MessageFuture produced no messages")
}
// Re-create the same sequence in a context and call the collector.
fakeFuture := newSliceFuture(msgs)
ctx := setArtifactCollector(context.Background(), fakeFuture)
got := collectArtifactsFromToolCalls(ctx, nil)
if len(got) != 1 {
t.Fatalf("collected %d artifacts, want 1", len(got))
}
if got[0].Name != "agent_artifact_bug_demo.png" {
t.Errorf("name=%q, want agent_artifact_bug_demo.png", got[0].Name)
}
if got[0].URL == "" {
t.Error("artifact URL is empty")
}
md := formatArtifactMarkdown(got, "done")
want := "![agent_artifact_bug_demo.png](/api/v1/documents/artifact/1ae8d553478544628bb8be267d502371.png)"
if !strings.Contains(md, want) {
t.Errorf("markdown=%q, want substring %q", md, want)
}
}
func drainFutureMessages(t *testing.T, future react.MessageFuture) []*schema.Message {
t.Helper()
var out []*schema.Message
iter := future.GetMessages()
for {
msg, ok, err := iter.Next()
if err != nil {
t.Fatalf("MessageFuture.Next: %v", err)
}
if !ok {
break
}
out = append(out, msg)
}
return out
}
// sliceFuture is a react.MessageFuture backed by a slice.
type sliceFuture struct {
iter *react.Iterator[*schema.Message]
}
func newSliceFuture(messages []*schema.Message) *sliceFuture {
// Re-run a real react agent whose model returns the supplied messages as
// tool-call / tool-response / final-answer sequence. This gives us a real
// react.Iterator populated by eino's own callback plumbing.
opt, future := react.WithMessageFuture()
// Extract any tool name referenced by the replayed messages so the agent's
// tool node can dispatch it.
toolName := "passthrough"
for _, m := range messages {
for _, tc := range m.ToolCalls {
if tc.Function.Name != "" {
toolName = tc.Function.Name
}
}
}
model := &replayModel{messages: messages}
agent, err := react.NewAgent(context.Background(), &react.AgentConfig{
ToolCallingModel: model,
ToolsConfig: compose.ToolsNodeConfig{
Tools: []tool.BaseTool{&passthroughTool{name: toolName}},
},
MaxStep: len(messages) + 1,
})
if err != nil {
panic(err)
}
_, err = agent.Generate(context.Background(), []*schema.Message{
schema.UserMessage("replay"),
}, opt)
if err != nil {
panic(err)
}
return &sliceFuture{iter: future.GetMessages()}
}
func (f *sliceFuture) GetMessages() *react.Iterator[*schema.Message] {
return f.iter
}
func (f *sliceFuture) GetMessageStreams() *react.Iterator[*schema.StreamReader[*schema.Message]] {
return nil
}
// replayModel replays a scripted sequence of messages on successive Generate calls.
type replayModel struct {
messages []*schema.Message
pos int
}
func (m *replayModel) Generate(_ context.Context, _ []*schema.Message, _ ...model.Option) (*schema.Message, error) {
if m.pos >= len(m.messages) {
return &schema.Message{Role: schema.Assistant, Content: "done"}, nil
}
msg := m.messages[m.pos]
m.pos++
return msg, nil
}
func (m *replayModel) Stream(_ context.Context, _ []*schema.Message, _ ...model.Option) (*schema.StreamReader[*schema.Message], error) {
sr, sw := schema.Pipe[*schema.Message](1)
sw.Close()
return sr, nil
}
func (m *replayModel) WithTools(tools []*schema.ToolInfo) (model.ToolCallingChatModel, error) {
return m, nil
}
// passthroughTool echoes its input as a tool result.
type passthroughTool struct {
name string
}
func (t *passthroughTool) Info(_ context.Context) (*schema.ToolInfo, error) {
return &schema.ToolInfo{
Name: t.name,
Desc: "echoes arguments",
ParamsOneOf: schema.NewParamsOneOfByParams(map[string]*schema.ParameterInfo{
"unused": {Type: schema.String},
}),
}, nil
}
func (t *passthroughTool) InvokableRun(_ context.Context, argumentsInJSON string, _ ...tool.Option) (string, error) {
return argumentsInJSON, nil
}