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fix(ai): consolidate consecutive tool_result messages for Claude and Gemini

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Anthropic and Gemini APIs require ALL tool_result blocks for a given
assistant message to be in a SINGLE user message that immediately follows
the assistant message. Previously, each tool AiMessage was converted to
a separate user message, causing Anthropic to reject multi-turn tool
conversations with 'tool_result must follow a tool_use block' error.

Fix: collect consecutive 'tool' role messages into a buffer, then flush
as a single user message with all tool_result/functionResponse blocks
when a non-tool message is encountered or at end of message list.

- Claude: merge N tool results into 1 user message with N content blocks
- Gemini: merge N tool results into 1 user message with N functionResponse parts
- OpenAI path unchanged (each tool message already has tool_call_id field)
This commit is contained in:
runstone committed 2026-06-12 12:49:49 +08:00
1 parent 453169ae45
commit 28fc4bc2a9
1 file changed
+66 -36
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crates/dbx-core/src/ai.rs
+66 -36
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@@ -1205,29 +1205,45 @@ async fn stream_claude_with_tools(
on_event: &impl Fn(StreamToolEvent),
) -> Result<(), String> {
let mut messages: Vec<serde_json::Value> = Vec::new();
let mut pending_tool_results: Vec<serde_json::Value> = Vec::new();
for m in &request.messages {
if m.role == "tool" {
messages.push(json!({
"role": "user",
"content": [{
"type": "tool_result",
"tool_use_id": m.tool_call_id.as_deref().unwrap_or_default(),
"content": m.content
}]
// Collect consecutive tool results; flush as a single user message.
pending_tool_results.push(json!({
"type": "tool_result",
"tool_use_id": m.tool_call_id.as_deref().unwrap_or_default(),
"content": m.content
}));
} else if m.role == "assistant" && !m.tool_calls.is_empty() {
let mut content_blocks: Vec<serde_json::Value> = Vec::new();
if !m.content.is_empty() {
content_blocks.push(json!({ "type": "text", "text": m.content }));
}
for tc in &m.tool_calls {
content_blocks.push(json!({ "type": "tool_use", "id": tc.id, "name": tc.name, "input": tc.arguments }));
}
messages.push(json!({ "role": "assistant", "content": content_blocks }));
} else {
messages.push(json!({ "role": m.role, "content": m.content }));
// Flush any pending tool results before emitting a non-tool message.
if !pending_tool_results.is_empty() {
messages.push(json!({
"role": "user",
"content": pending_tool_results.drain(..).collect::<Vec<_>>()
}));
}
if m.role == "assistant" && !m.tool_calls.is_empty() {
let mut content_blocks: Vec<serde_json::Value> = Vec::new();
if !m.content.is_empty() {
content_blocks.push(json!({ "type": "text", "text": m.content }));
}
for tc in &m.tool_calls {
content_blocks
.push(json!({ "type": "tool_use", "id": tc.id, "name": tc.name, "input": tc.arguments }));
}
messages.push(json!({ "role": "assistant", "content": content_blocks }));
} else {
messages.push(json!({ "role": m.role, "content": m.content }));
}
}
}
// Flush any remaining tool results at the end of the message list.
if !pending_tool_results.is_empty() {
messages.push(json!({
"role": "user",
"content": pending_tool_results.drain(..).collect::<Vec<_>>()
}));
}
let tool_json: Vec<serde_json::Value> = tools.iter().map(|t| t.to_anthropic_tool()).collect();
@@ -1492,6 +1508,7 @@ async fn stream_gemini_with_tools(
on_event: &impl Fn(StreamToolEvent),
) -> Result<(), String> {
let mut contents: Vec<serde_json::Value> = Vec::new();
let mut pending_function_responses: Vec<serde_json::Value> = Vec::new();
for m in &request.messages {
if m.role == "tool" {
let tool_name = m
@@ -1500,29 +1517,42 @@ async fn stream_gemini_with_tools(
.and_then(|s| s.strip_prefix("gemini-tc-"))
.and_then(|s| s.rsplitn(2, '-').nth(1))
.unwrap_or("unknown");
contents.push(json!({
"role": "user",
"parts": [{
"functionResponse": {
"name": tool_name,
"response": { "content": m.content }
}
}]
pending_function_responses.push(json!({
"functionResponse": {
"name": tool_name,
"response": { "content": m.content }
}
}));
} else if m.role == "assistant" && !m.tool_calls.is_empty() {
let mut parts: Vec<serde_json::Value> = Vec::new();
if !m.content.is_empty() {
parts.push(json!({ "text": m.content }));
}
for tc in &m.tool_calls {
parts.push(json!({ "functionCall": { "name": tc.name, "args": tc.arguments } }));
}
contents.push(json!({ "role": "model", "parts": parts }));
} else {
let role = if m.role == "assistant" { "model" } else { "user" };
contents.push(json!({ "role": role, "parts": [{ "text": m.content }] }));
// Flush any pending function responses before emitting a non-tool message.
if !pending_function_responses.is_empty() {
contents.push(json!({
"role": "user",
"parts": pending_function_responses.drain(..).collect::<Vec<_>>()
}));
}
if m.role == "assistant" && !m.tool_calls.is_empty() {
let mut parts: Vec<serde_json::Value> = Vec::new();
if !m.content.is_empty() {
parts.push(json!({ "text": m.content }));
}
for tc in &m.tool_calls {
parts.push(json!({ "functionCall": { "name": tc.name, "args": tc.arguments } }));
}
contents.push(json!({ "role": "model", "parts": parts }));
} else {
let role = if m.role == "assistant" { "model" } else { "user" };
contents.push(json!({ "role": role, "parts": [{ "text": m.content }] }));
}
}
}
// Flush any remaining function responses at the end of the message list.
if !pending_function_responses.is_empty() {
contents.push(json!({
"role": "user",
"parts": pending_function_responses.drain(..).collect::<Vec<_>>()
}));
}
let tool_declarations: Vec<serde_json::Value> = tools.iter().map(|t| t.to_gemini_tool()).collect();