feat(ai-pipeline): 支持 reasoning signature 及媒体内容块的跨格式流式转换

- 在 CanonicalStreamEvent 中新增 ReasoningSignature 和 ContentPart 变体，CanonicalContentPart 枚举覆盖图片/文件/音频
- Gemini 流解析器提取 thoughtSignature，并对 inlineData/fileData 等非文本 part 生成 ContentPart 事件
- Claude 流聚合支持 thinking_delta / signature_delta，输出 thinking block 携带 signature 字段
- Gemini 同步响应聚合重写，支持媒体 part 和 reasoning signature 的完整还原
- 跨格式矩阵（gemini↔claude↔openai）补全图片块双向转换及 reasoning signature 传递
- 请求转换层（to/from openai_chat）补全 Claude/Gemini 的 thinking、图片、工具调用字段映射
- 新增/扩展测试：inline image 双向重写、thinking signature 聚合、跨格式 sync product 媒体字段

apps/aether-gateway/src/ai_pipeline/finalize/tests_sync.rs

@@ -888,6 +888,7 @@ fn converts_claude_cli_tool_use_to_openai_cli_function_call() {
                 },
                 {
                     "type": "function_call",
+                    "id": "tool_123",
                     "call_id": "tool_123",
                     "name": "read_file",
                     "arguments": "{\"path\":\"/tmp/test.txt\"}"
@@ -952,7 +953,10 @@ fn converts_gemini_cli_response_to_openai_cli_response() {
             "usage": {
                 "input_tokens": 3,
                 "output_tokens": 7,
-                "total_tokens": 10
+                "total_tokens": 10,
+                "output_tokens_details": {
+                    "reasoning_tokens": 2
+                }
             }
         })
     );
@@ -1011,6 +1015,7 @@ fn converts_gemini_cli_function_call_to_openai_cli_function_call() {
                 },
                 {
                     "type": "function_call",
+                    "id": "call_auto_1",
                     "call_id": "call_auto_1",
                     "name": "get_weather",
                     "arguments": "{\"location\":\"Tokyo\"}"
@@ -1019,7 +1024,10 @@ fn converts_gemini_cli_function_call_to_openai_cli_function_call() {
             "usage": {
                 "input_tokens": 3,
                 "output_tokens": 7,
-                "total_tokens": 10
+                "total_tokens": 10,
+                "output_tokens_details": {
+                    "reasoning_tokens": 2
+                }
             }
         })
     );

apps/aether-gateway/src/handlers/admin/provider/pool/runtime/writes.rs

@@ -886,7 +886,7 @@ mod tests {
         record_admin_provider_pool_stream_timeout(&runner, "provider-1", "key-4", &pool_config)
             .await;
 
-        let runtime = read_admin_provider_pool_runtime_state(
+        let mut runtime = read_admin_provider_pool_runtime_state(
             &runner,
             "provider-1",
             &key_ids,
@@ -894,6 +894,25 @@ mod tests {
             None,
         )
         .await;
+        for _ in 0..20 {
+            if runtime
+                .cooldown_reason_by_key
+                .get("key-4")
+                .map(String::as_str)
+                == Some("stream_timeout_x2")
+            {
+                break;
+            }
+            tokio::time::sleep(std::time::Duration::from_millis(10)).await;
+            runtime = read_admin_provider_pool_runtime_state(
+                &runner,
+                "provider-1",
+                &key_ids,
+                &pool_config,
+                None,
+            )
+            .await;
+        }
 
         assert_eq!(
             runtime

apps/aether-gateway/src/tests/ai_execute/finalize_local.rs

@@ -877,7 +877,7 @@ async fn gateway_executes_openai_chat_cross_format_upstream_stream_via_local_fin
                 "index": 0,
                 "message": {
                     "role": "assistant",
-                    "content": "Gemini Chat"
+                    "content": "Hello Gemini Chat"
                 },
                 "finish_reason": "stop"
             }],

apps/aether-gateway/src/tests/ai_execute/finalize_local_cli/cross_format.rs

@@ -860,6 +860,7 @@ async fn gateway_executes_openai_cli_cross_format_function_call_upstream_stream_
                 },
                 {
                     "type": "function_call",
+                    "id": "call_auto_1",
                     "call_id": "call_auto_1",
                     "name": "get_weather",
                     "arguments": "{\"location\":\"Tokyo\"}"
@@ -1410,13 +1411,13 @@ async fn gateway_executes_openai_cli_antigravity_cross_format_upstream_stream_vi
     assert_eq!(
         response_json,
         json!({
-            "id": "resp_antigravity_cli_xfmt_123",
+            "id": "resp-local-stream",
             "object": "response",
             "status": "completed",
             "model": "claude-sonnet-4-5",
             "output": [{
                 "type": "message",
-                "id": "resp_antigravity_cli_xfmt_123_msg",
+                "id": "resp-local-stream_msg",
                 "role": "assistant",
                 "status": "completed",
                 "content": [{

apps/aether-gateway/src/tests/ai_execute/finalize_local_provider/gemini.rs

@@ -912,6 +912,7 @@ async fn gateway_executes_gemini_chat_sync_upstream_stream_via_local_finalize_re
     assert_eq!(
         response_json,
         json!({
+            "responseId": "resp-local-stream",
             "candidates": [{
                 "content": {
                     "parts": [{"text": "Hello Gemini"}],
@@ -1972,10 +1973,18 @@ async fn gateway_executes_antigravity_gemini_cli_sync_upstream_stream_via_local_
     assert_eq!(
         response_json,
         json!({
+            "responseId": "resp-local-stream",
             "_v1internal_response_id": "resp_antigravity_cli_sync_123",
             "candidates": [{
                 "content": {
                     "parts": [
+                        {
+                            "functionCall": {
+                                "name": "get_weather",
+                                "args": {"city": "SF"},
+                                "id": "call_get_weather_0"
+                            }
+                        },
                         {"text": "Hello Antigravity CLI"},
                         {
                             "functionCall": {

apps/aether-gateway/src/tests/ai_execute/sync/gemini/cli.rs

@@ -2115,6 +2115,7 @@ async fn gateway_executes_antigravity_gemini_cli_sync_via_local_decision_gate_af
     assert_eq!(
         response_json,
         json!({
+            "responseId": "resp-local-stream",
             "_v1internal_response_id": "resp_antigravity_cli_local_sync_123",
             "candidates": [{
                 "content": {

apps/aether-gateway/src/tests/usage/local.rs

@@ -36,7 +36,7 @@ where
     let mut stored = None;
     // Usage terminal events are written on a shared background runtime; under full-suite parallel
     // load they can lag noticeably behind the request/response assertion path.
-    let timeout = std::time::Duration::from_secs(30);
+    let timeout = std::time::Duration::from_secs(60);
     let deadline = tokio::time::Instant::now() + timeout;
     loop {
         stored = repository

crates/aether-ai-pipeline/src/conversion/request/from_openai_chat/claude.rs

@@ -5,8 +5,8 @@ use super::super::to_openai_chat::{extract_openai_text_content, parse_openai_too
 use super::shared::parse_openai_tool_arguments;
 use crate::planner::openai::{
     copy_request_number_field, extract_openai_reasoning_effort,
-    map_openai_reasoning_effort_to_thinking_budget, parse_openai_stop_sequences,
+    map_openai_reasoning_effort_to_claude_output, map_openai_reasoning_effort_to_thinking_budget,
-    resolve_openai_chat_max_tokens,
+    parse_openai_stop_sequences, resolve_openai_chat_max_tokens,
 };
 
 pub fn convert_openai_chat_request_to_claude_request(
@@ -37,17 +37,18 @@ pub fn convert_openai_chat_request_to_claude_request(
                 "user" => {
                     let blocks = convert_openai_content_to_claude_blocks(
                         message_object.get("content"),
-                        true,
+                        ClaudeMessageRole::User,
                     )?;
                     if !blocks.is_empty() {
                         messages.push(build_claude_message("user", blocks));
                     }
                 }
                 "assistant" => {
-                    let mut blocks = convert_openai_content_to_claude_blocks(
+                    let mut blocks = extract_openai_reasoning_to_claude_blocks(message_object);
+                    blocks.extend(convert_openai_content_to_claude_blocks(
                         message_object.get("content"),
-                        false,
+                        ClaudeMessageRole::Assistant,
-                    )?;
+                    )?);
                     if let Some(tool_calls) =
                         message_object.get("tool_calls").and_then(Value::as_array)
                     {
@@ -159,14 +160,30 @@ pub fn convert_openai_chat_request_to_claude_request(
                 }),
             );
         }
+        if let Some(output_effort) =
+            map_openai_reasoning_effort_to_claude_output(reasoning_effort.as_str())
+        {
+            output.insert(
+                "output_config".to_string(),
+                json!({
+                    "effort": output_effort,
+                }),
+            );
+        }
     }
 
     Some(Value::Object(output))
 }
 
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+enum ClaudeMessageRole {
+    User,
+    Assistant,
+}
+
 fn convert_openai_content_to_claude_blocks(
     content: Option<&Value>,
-    allow_images: bool,
+    role: ClaudeMessageRole,
 ) -> Option<Vec<Value>> {
     match content {
         None | Some(Value::Null) => Some(Vec::new()),
@@ -187,14 +204,14 @@ fn convert_openai_content_to_claude_blocks(
                     .and_then(Value::as_str)
                     .unwrap_or_default();
                 match part_type {
-                    "text" | "input_text" => {
+                    "text" | "input_text" | "output_text" => {
                         if let Some(text) = part_object.get("text").and_then(Value::as_str) {
                             if !text.trim().is_empty() {
                                 blocks.push(json!({ "type": "text", "text": text }));
                             }
                         }
                     }
-                    "image_url" | "input_image" if allow_images => {
+                    "image_url" | "input_image" | "output_image" => {
                         let url = part_object
                             .get("image_url")
                             .and_then(|value| {
@@ -206,7 +223,14 @@ fn convert_openai_content_to_claude_blocks(
                                         .map(ToOwned::to_owned)
                                 })
                             })
+                            .or_else(|| {
+                                part_object
+                                    .get("url")
+                                    .and_then(Value::as_str)
+                                    .map(ToOwned::to_owned)
+                            })
                             .filter(|value| !value.trim().is_empty())?;
+                        if role == ClaudeMessageRole::User {
                             if let Some((media_type, data)) = parse_data_url(url.as_str()) {
                                 blocks.push(json!({
                                     "type": "image",
@@ -225,6 +249,12 @@ fn convert_openai_content_to_claude_blocks(
                                     }
                                 }));
                             }
+                        } else {
+                            blocks.push(json!({
+                                "type": "text",
+                                "text": assistant_image_placeholder(url.as_str()),
+                            }));
+                        }
                     }
                     "file" | "input_file" => {
                         let file_object = part_object
@@ -244,6 +274,42 @@ fn convert_openai_content_to_claude_blocks(
                                     }
                                 }));
                             }
+                        } else if let Some(file_id) = file_object
+                            .get("file_id")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty())
+                        {
+                            blocks.push(json!({
+                                "type": "text",
+                                "text": format!("[File: {file_id}]"),
+                            }));
+                        }
+                    }
+                    "input_audio" => {
+                        let audio_object = part_object
+                            .get("input_audio")
+                            .and_then(Value::as_object)
+                            .unwrap_or(part_object);
+                        let data = audio_object
+                            .get("data")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty());
+                        let format = audio_object
+                            .get("format")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty());
+                        if let (Some(data), Some(format)) = (data, format) {
+                            blocks.push(json!({
+                                "type": "document",
+                                "source": {
+                                    "type": "base64",
+                                    "media_type": format!("audio/{format}"),
+                                    "data": data,
+                                }
+                            }));
                         }
                     }
                     _ => {}
@@ -255,6 +321,77 @@ fn convert_openai_content_to_claude_blocks(
     }
 }
 
+fn extract_openai_reasoning_to_claude_blocks(message: &Map<String, Value>) -> Vec<Value> {
+    let mut blocks = Vec::new();
+    if let Some(reasoning_parts) = message.get("reasoning_parts").and_then(Value::as_array) {
+        for reasoning_part in reasoning_parts {
+            let Some(reasoning_object) = reasoning_part.as_object() else {
+                continue;
+            };
+            match reasoning_object
+                .get("type")
+                .and_then(Value::as_str)
+                .unwrap_or("thinking")
+            {
+                "thinking" => {
+                    let thinking = reasoning_object
+                        .get("thinking")
+                        .or_else(|| reasoning_object.get("text"))
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .unwrap_or_default();
+                    if thinking.is_empty() {
+                        continue;
+                    }
+                    let mut block = Map::new();
+                    block.insert("type".to_string(), Value::String("thinking".to_string()));
+                    block.insert("thinking".to_string(), Value::String(thinking.to_string()));
+                    if let Some(signature) = reasoning_object
+                        .get("signature")
+                        .and_then(Value::as_str)
+                        .filter(|value| !value.is_empty())
+                    {
+                        block.insert(
+                            "signature".to_string(),
+                            Value::String(signature.to_string()),
+                        );
+                    }
+                    blocks.push(Value::Object(block));
+                }
+                "redacted_thinking" => {
+                    let data = reasoning_object
+                        .get("data")
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .unwrap_or_default();
+                    if !data.is_empty() {
+                        blocks.push(json!({
+                            "type": "redacted_thinking",
+                            "data": data,
+                        }));
+                    }
+                }
+                _ => {}
+            }
+        }
+    }
+    if !blocks.is_empty() {
+        return blocks;
+    }
+    if let Some(reasoning_content) = message
+        .get("reasoning_content")
+        .and_then(Value::as_str)
+        .map(str::trim)
+        .filter(|value| !value.is_empty())
+    {
+        blocks.push(json!({
+            "type": "thinking",
+            "thinking": reasoning_content,
+        }));
+    }
+    blocks
+}
+
 fn convert_openai_tools_to_claude(
     tools: Option<&Value>,
     web_search_options: Option<&Value>,
@@ -491,6 +628,14 @@ fn parse_data_url(value: &str) -> Option<(String, String)> {
     Some((media_type.to_string(), data.to_string()))
 }
 
+fn assistant_image_placeholder(url: &str) -> String {
+    if url.starts_with("data:") {
+        "[Image]".to_string()
+    } else {
+        format!("[Image: {url}]")
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::convert_openai_chat_request_to_claude_request;
@@ -555,4 +700,115 @@ mod tests {
             })
         );
     }
+
+    #[test]
+    fn converts_openai_multipart_reasoning_and_file_id_to_claude_request() {
+        let request = json!({
+            "model": "gpt-5.4",
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        { "type": "text", "text": "Read this" },
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": "data:image/png;base64,iVBORw0KGgo="
+                            }
+                        },
+                        {
+                            "type": "file",
+                            "file": {
+                                "file_data": "data:application/pdf;base64,JVBERi0x"
+                            }
+                        }
+                    ]
+                },
+                {
+                    "role": "assistant",
+                    "reasoning_content": "step by step",
+                    "reasoning_parts": [
+                        {
+                            "type": "thinking",
+                            "thinking": "step by step",
+                            "signature": "sig_123"
+                        },
+                        {
+                            "type": "redacted_thinking",
+                            "data": "redacted_blob"
+                        }
+                    ],
+                    "content": [
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": "https://example.com/diagram.png"
+                            }
+                        },
+                        { "type": "file", "file": { "file_id": "file_123" } },
+                        { "type": "text", "text": "done" }
+                    ],
+                    "tool_calls": [{
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {
+                            "name": "lookup",
+                            "arguments": "\"tokyo\""
+                        }
+                    }]
+                }
+            ],
+            "reasoning_effort": "xhigh"
+        });
+
+        let converted =
+            convert_openai_chat_request_to_claude_request(&request, "claude-sonnet-4-5", false)
+                .expect("request should convert");
+
+        assert_eq!(
+            converted["messages"][0]["content"],
+            json!([
+                { "type": "text", "text": "Read this" },
+                {
+                    "type": "image",
+                    "source": {
+                        "type": "base64",
+                        "media_type": "image/png",
+                        "data": "iVBORw0KGgo="
+                    }
+                },
+                {
+                    "type": "document",
+                    "source": {
+                        "type": "base64",
+                        "media_type": "application/pdf",
+                        "data": "JVBERi0x"
+                    }
+                }
+            ])
+        );
+        assert_eq!(converted["messages"][1]["content"][0]["type"], "thinking");
+        assert_eq!(
+            converted["messages"][1]["content"][0]["signature"],
+            "sig_123"
+        );
+        assert_eq!(
+            converted["messages"][1]["content"][1]["type"],
+            "redacted_thinking"
+        );
+        assert_eq!(
+            converted["messages"][1]["content"][2]["text"],
+            "[Image: https://example.com/diagram.png]"
+        );
+        assert_eq!(
+            converted["messages"][1]["content"][3]["text"],
+            "[File: file_123]"
+        );
+        assert_eq!(
+            converted["messages"][1]["content"][5]["input"],
+            json!({"raw": "tokyo"})
+        );
+        assert_eq!(converted["thinking"]["budget_tokens"], 8192);
+        assert_eq!(converted["output_config"]["effort"], "max");
+    }
 }

crates/aether-ai-pipeline/src/conversion/request/from_openai_chat/gemini.rs

@@ -39,7 +39,7 @@ pub fn convert_openai_chat_request_to_gemini_request(
                 "user" => {
                     let parts = convert_openai_content_to_gemini_parts(
                         message_object.get("content"),
-                        true,
+                        OpenAiToGeminiRole::User,
                     )?;
                     if !parts.is_empty() {
                         contents.push(json!({
@@ -51,8 +51,12 @@ pub fn convert_openai_chat_request_to_gemini_request(
                 "assistant" => {
                     let mut parts = convert_openai_content_to_gemini_parts(
                         message_object.get("content"),
-                        false,
+                        OpenAiToGeminiRole::Assistant,
                     )?;
+                    let reasoning_parts = extract_openai_reasoning_to_gemini_parts(message_object);
+                    if !reasoning_parts.is_empty() {
+                        parts.splice(0..0, reasoning_parts);
+                    }
                     if let Some(tool_calls) =
                         message_object.get("tool_calls").and_then(Value::as_array)
                     {
@@ -249,14 +253,105 @@ pub fn convert_openai_chat_request_to_gemini_request(
                     .or_insert(thinking_config);
             }
         }
+        if let Some(gemini) = extra_body.get("gemini").and_then(Value::as_object) {
+            let existing = output
+                .entry("generationConfig".to_string())
+                .or_insert_with(|| Value::Object(Map::new()))
+                .as_object_mut()?;
+            if let Some(extra_config) = gemini
+                .get("generation_config_extra")
+                .or_else(|| gemini.get("generationConfigExtra"))
+                .and_then(Value::as_object)
+            {
+                for (key, value) in extra_config {
+                    existing.entry(key.clone()).or_insert_with(|| value.clone());
+                }
+            }
+            if let Some(safety_settings) = gemini
+                .get("safety_settings")
+                .or_else(|| gemini.get("safetySettings"))
+                .cloned()
+            {
+                output.insert("safetySettings".to_string(), safety_settings);
+            }
+            if let Some(cached_content) = gemini
+                .get("cached_content")
+                .or_else(|| gemini.get("cachedContent"))
+                .cloned()
+            {
+                output.insert("cachedContent".to_string(), cached_content);
+            }
+        }
     }
 
     Some(Value::Object(output))
 }
 
+fn extract_openai_reasoning_to_gemini_parts(message: &Map<String, Value>) -> Vec<Value> {
+    let mut parts = Vec::new();
+    if let Some(reasoning_parts) = message.get("reasoning_parts").and_then(Value::as_array) {
+        for reasoning_part in reasoning_parts {
+            let Some(reasoning_object) = reasoning_part.as_object() else {
+                continue;
+            };
+            if reasoning_object
+                .get("type")
+                .and_then(Value::as_str)
+                .is_some_and(|value| value != "thinking")
+            {
+                continue;
+            }
+            let thinking = reasoning_object
+                .get("thinking")
+                .or_else(|| reasoning_object.get("text"))
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .unwrap_or_default();
+            if thinking.is_empty() {
+                continue;
+            }
+            let mut part = Map::new();
+            part.insert("text".to_string(), Value::String(thinking.to_string()));
+            part.insert("thought".to_string(), Value::Bool(true));
+            if let Some(signature) = reasoning_object
+                .get("signature")
+                .and_then(Value::as_str)
+                .filter(|value| !value.is_empty())
+            {
+                part.insert(
+                    "thoughtSignature".to_string(),
+                    Value::String(signature.to_string()),
+                );
+            }
+            parts.push(Value::Object(part));
+        }
+    }
+    if !parts.is_empty() {
+        return parts;
+    }
+    if let Some(reasoning_content) = message
+        .get("reasoning_content")
+        .and_then(Value::as_str)
+        .map(str::trim)
+        .filter(|value| !value.is_empty())
+    {
+        parts.push(json!({
+            "text": reasoning_content,
+            "thought": true,
+        }));
+    }
+    parts
+}
+
+#[derive(Debug, Clone, Copy, PartialEq, Eq)]
+enum OpenAiToGeminiRole {
+    User,
+    Assistant,
+}
+
 fn convert_openai_content_to_gemini_parts(
     content: Option<&Value>,
-    allow_images: bool,
+    _role: OpenAiToGeminiRole,
 ) -> Option<Vec<Value>> {
     match content {
         None | Some(Value::Null) => Some(Vec::new()),
@@ -277,14 +372,14 @@ fn convert_openai_content_to_gemini_parts(
                     .and_then(Value::as_str)
                     .unwrap_or_default();
                 match part_type {
-                    "text" | "input_text" => {
+                    "text" | "input_text" | "output_text" => {
                         if let Some(text) = part_object.get("text").and_then(Value::as_str) {
                             if !text.trim().is_empty() {
                                 converted.push(json!({ "text": text }));
                             }
                         }
                     }
-                    "image_url" | "input_image" if allow_images => {
+                    "image_url" | "input_image" | "output_image" => {
                         let image = part_object
                             .get("image_url")
                             .and_then(|value| {
@@ -334,6 +429,39 @@ fn convert_openai_content_to_gemini_parts(
                                     }
                                 }));
                             }
+                        } else if let Some(file_id) = file_object
+                            .get("file_id")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty())
+                        {
+                            converted.push(json!({
+                                "text": format!("[File: {file_id}]"),
+                            }));
+                        }
+                    }
+                    "input_audio" => {
+                        let audio_object = part_object
+                            .get("input_audio")
+                            .and_then(Value::as_object)
+                            .unwrap_or(part_object);
+                        let data = audio_object
+                            .get("data")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty());
+                        let format = audio_object
+                            .get("format")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty());
+                        if let (Some(data), Some(format)) = (data, format) {
+                            converted.push(json!({
+                                "inlineData": {
+                                    "mimeType": format!("audio/{format}"),
+                                    "data": data,
+                                }
+                            }));
                         }
                     }
                     _ => {}
@@ -1137,4 +1265,143 @@ mod tests {
         assert_eq!(tools.len(), 1);
         assert_eq!(tools[0], json!({ "googleSearch": {} }));
     }
+
+    #[test]
+    fn converts_openai_reasoning_multimodal_and_passthrough_to_gemini_request() {
+        let request = json!({
+            "model": "gpt-5.4",
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        { "type": "text", "text": "Read this" },
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": "data:image/png;base64,iVBORw0KGgo="
+                            }
+                        },
+                        {
+                            "type": "file",
+                            "file": {
+                                "file_data": "data:application/pdf;base64,JVBERi0x"
+                            }
+                        },
+                        {
+                            "type": "input_audio",
+                            "input_audio": {
+                                "data": "SUQz",
+                                "format": "mp3"
+                            }
+                        }
+                    ]
+                },
+                {
+                    "role": "assistant",
+                    "reasoning_content": "step by step",
+                    "reasoning_parts": [
+                        {
+                            "type": "thinking",
+                            "thinking": "step by step",
+                            "signature": "sig_123"
+                        }
+                    ],
+                    "content": [
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": "https://example.com/cat.png"
+                            }
+                        },
+                        {
+                            "type": "file",
+                            "file": { "file_id": "file_123" }
+                        },
+                        { "type": "text", "text": "done" }
+                    ],
+                    "tool_calls": [{
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {
+                            "name": "lookup",
+                            "arguments": "\"tokyo\""
+                        }
+                    }]
+                }
+            ],
+            "reasoning_effort": "high",
+            "extra_body": {
+                "google": {
+                    "response_modalities": ["TEXT", "IMAGE"],
+                    "thinking_config": {
+                        "includeThoughts": true,
+                        "thinkingBudget": 2048
+                    }
+                },
+                "gemini": {
+                    "generation_config_extra": {
+                        "presencePenalty": 0.5
+                    },
+                    "safety_settings": [
+                        { "category": "HARM_CATEGORY_HATE_SPEECH" }
+                    ],
+                    "cached_content": "cached/abc"
+                }
+            }
+        });
+
+        let converted =
+            convert_openai_chat_request_to_gemini_request(&request, "gemini-2.5-pro", false)
+                .expect("request should convert");
+
+        assert_eq!(
+            converted["contents"][0],
+            json!({
+                "role": "user",
+                "parts": [
+                    { "text": "Read this" },
+                    { "inlineData": { "mimeType": "image/png", "data": "iVBORw0KGgo=" } },
+                    { "inlineData": { "mimeType": "application/pdf", "data": "JVBERi0x" } },
+                    { "inlineData": { "mimeType": "audio/mp3", "data": "SUQz" } }
+                ]
+            })
+        );
+        assert_eq!(converted["contents"][1]["role"], "model");
+        assert_eq!(converted["contents"][1]["parts"][0]["thought"], true);
+        assert_eq!(
+            converted["contents"][1]["parts"][0]["thoughtSignature"],
+            "sig_123"
+        );
+        assert_eq!(
+            converted["contents"][1]["parts"][1],
+            json!({
+                "fileData": {
+                    "fileUri": "https://example.com/cat.png",
+                    "mimeType": "image/png"
+                }
+            })
+        );
+        assert_eq!(
+            converted["contents"][1]["parts"][2]["text"],
+            "[File: file_123]"
+        );
+        assert_eq!(
+            converted["contents"][1]["parts"][4]["functionCall"]["args"],
+            json!({ "raw": "tokyo" })
+        );
+        assert_eq!(
+            converted["generationConfig"]["thinkingConfig"]["thinkingBudget"],
+            4096
+        );
+        assert_eq!(
+            converted["generationConfig"]["responseModalities"],
+            json!(["TEXT", "IMAGE"])
+        );
+        assert_eq!(converted["generationConfig"]["presencePenalty"], 0.5);
+        assert_eq!(
+            converted["safetySettings"],
+            json!([{ "category": "HARM_CATEGORY_HATE_SPEECH" }])
+        );
+        assert_eq!(converted["cachedContent"], "cached/abc");
+    }
 }

crates/aether-ai-pipeline/src/conversion/request/from_openai_chat/shared.rs

@@ -10,12 +10,12 @@ pub(super) fn parse_openai_tool_arguments(arguments: Option<&Value>) -> Option<V
             } else {
                 match serde_json::from_str::<Value>(trimmed) {
                     Ok(Value::Object(object)) => Some(Value::Object(object)),
-                    Ok(other) => Some(json!({ "input": other })),
+                    Ok(other) => Some(json!({ "raw": other })),
-                    Err(_) => Some(json!({ "input": trimmed })),
+                    Err(_) => Some(json!({ "raw": trimmed })),
                 }
             }
         }
-        Some(other) => Some(json!({ "input": other })),
+        Some(other) => Some(json!({ "raw": other })),
         None => Some(json!({})),
     }
 }

crates/aether-ai-pipeline/src/conversion/request/to_openai_chat/claude.rs

@@ -32,82 +32,16 @@ pub fn normalize_claude_request_to_openai_chat_request(body_json: &Value) -> Opt
                 .to_ascii_lowercase();
             match role.as_str() {
                 "user" => {
-                    let mut text_segments = Vec::new();
+                    append_claude_user_message_to_openai_messages(
-                    if let Some(content) = message_object.get("content") {
+                        message_object.get("content"),
-                        for block in normalize_claude_content_blocks(content)? {
+                        &mut messages,
-                            match block {
+                    )?;
-                                ClaudeNormalizedBlock::Text(text) => {
-                                    if !text.trim().is_empty() {
-                                        text_segments.push(text);
-                                    }
-                                }
-                                ClaudeNormalizedBlock::ToolResult {
-                                    tool_use_id,
-                                    content,
-                                } => {
-                                    messages.push(json!({
-                                        "role": "tool",
-                                        "tool_call_id": tool_use_id,
-                                        "content": content,
-                                    }));
-                                }
-                                ClaudeNormalizedBlock::ToolUse { .. } => {}
-                            }
-                        }
-                    }
-                    let text = text_segments.join("\n\n");
-                    if !text.trim().is_empty() {
-                        messages.push(json!({
-                            "role": "user",
-                            "content": text,
-                        }));
-                    }
                 }
                 "assistant" => {
-                    let mut text_segments = Vec::new();
+                    messages.push(normalize_claude_assistant_message_to_openai_message(
-                    let mut tool_calls = Vec::new();
+                        message_object.get("content"),
-                    if let Some(content) = message_object.get("content") {
+                        &mut next_generated_tool_use_index,
-                        for block in normalize_claude_content_blocks(content)? {
+                    )?);
-                            match block {
-                                ClaudeNormalizedBlock::Text(text) => {
-                                    if !text.trim().is_empty() {
-                                        text_segments.push(text);
-                                    }
-                                }
-                                ClaudeNormalizedBlock::ToolUse { id, name, input } => {
-                                    let tool_use_id = id.unwrap_or_else(|| {
-                                        let generated =
-                                            format!("toolu_auto_{next_generated_tool_use_index}");
-                                        next_generated_tool_use_index += 1;
-                                        generated
-                                    });
-                                    tool_calls.push(json!({
-                                        "id": tool_use_id,
-                                        "type": "function",
-                                        "function": {
-                                            "name": name,
-                                            "arguments": canonical_json_string(input.unwrap_or(Value::Object(Map::new()))),
-                                        }
-                                    }));
-                                }
-                                ClaudeNormalizedBlock::ToolResult { .. } => {}
-                            }
-                        }
-                    }
-                    let mut assistant = Map::new();
-                    assistant.insert("role".to_string(), Value::String("assistant".to_string()));
-                    assistant.insert(
-                        "content".to_string(),
-                        if text_segments.is_empty() && !tool_calls.is_empty() {
-                            Value::Null
-                        } else {
-                            Value::String(text_segments.join("\n\n"))
-                        },
-                    );
-                    if !tool_calls.is_empty() {
-                        assistant.insert("tool_calls".to_string(), Value::Array(tool_calls));
-                    }
-                    messages.push(Value::Object(assistant));
                 }
                 _ => {}
             }
@@ -123,8 +57,22 @@ pub fn normalize_claude_request_to_openai_chat_request(body_json: &Value) -> Opt
             output.insert(passthrough_key.to_string(), value.clone());
         }
     }
+    if output.get("stop").is_none() {
+        if let Some(stop_sequences) = request
+            .get("stop_sequences")
+            .cloned()
+            .filter(|value| !value.is_null())
+        {
+            output.insert("stop".to_string(), stop_sequences);
+        }
+    }
     if output.get("reasoning_effort").is_none() {
-        if let Some(thinking_budget) = request
+        if let Some(reasoning_effort) = extract_claude_output_reasoning_effort(request) {
+            output.insert(
+                "reasoning_effort".to_string(),
+                Value::String(reasoning_effort.to_string()),
+            );
+        } else if let Some(thinking_budget) = request
             .get("thinking")
             .and_then(Value::as_object)
             .and_then(|thinking| thinking.get("budget_tokens"))
@@ -162,6 +110,16 @@ pub fn normalize_claude_request_to_openai_chat_request(body_json: &Value) -> Opt
 #[derive(Debug)]
 enum ClaudeNormalizedBlock {
     Text(String),
+    Thinking {
+        text: String,
+        signature: Option<String>,
+    },
+    RedactedThinking {
+        data: String,
+    },
+    ImageUrl(String),
+    FileData(String),
+    FileUrl(String),
     ToolUse {
         id: Option<String>,
         name: String,
@@ -181,13 +139,97 @@ fn normalize_claude_content_blocks(content: &Value) -> Option<Vec<ClaudeNormaliz
             for block in blocks {
                 let block = block.as_object()?;
                 match block.get("type")?.as_str()? {
-                    "text" | "thinking" => {
+                    "text" => {
                         let text = block
                             .get("text")
                             .and_then(Value::as_str)
                             .unwrap_or_default();
                         normalized.push(ClaudeNormalizedBlock::Text(text.to_string()));
                     }
+                    "thinking" => {
+                        let thinking = block
+                            .get("thinking")
+                            .and_then(Value::as_str)
+                            .or_else(|| block.get("text").and_then(Value::as_str))
+                            .unwrap_or_default();
+                        normalized.push(ClaudeNormalizedBlock::Thinking {
+                            text: thinking.to_string(),
+                            signature: block
+                                .get("signature")
+                                .and_then(Value::as_str)
+                                .filter(|value| !value.is_empty())
+                                .map(ToOwned::to_owned),
+                        });
+                    }
+                    "redacted_thinking" => {
+                        let data = block
+                            .get("data")
+                            .and_then(Value::as_str)
+                            .unwrap_or_default();
+                        normalized.push(ClaudeNormalizedBlock::RedactedThinking {
+                            data: data.to_string(),
+                        });
+                    }
+                    "image" => {
+                        let source = block.get("source")?.as_object()?;
+                        match source.get("type")?.as_str()? {
+                            "base64" => {
+                                let media_type = source
+                                    .get("media_type")
+                                    .and_then(Value::as_str)
+                                    .map(str::trim)
+                                    .filter(|value| !value.is_empty())?;
+                                let data = source
+                                    .get("data")
+                                    .and_then(Value::as_str)
+                                    .map(str::trim)
+                                    .filter(|value| !value.is_empty())?;
+                                normalized.push(ClaudeNormalizedBlock::ImageUrl(build_data_url(
+                                    media_type, data,
+                                )));
+                            }
+                            "url" => {
+                                let url = source
+                                    .get("url")
+                                    .and_then(Value::as_str)
+                                    .map(str::trim)
+                                    .filter(|value| !value.is_empty())?
+                                    .to_string();
+                                normalized.push(ClaudeNormalizedBlock::ImageUrl(url));
+                            }
+                            _ => {}
+                        }
+                    }
+                    "document" => {
+                        let source = block.get("source")?.as_object()?;
+                        match source.get("type")?.as_str()? {
+                            "base64" => {
+                                let media_type = source
+                                    .get("media_type")
+                                    .and_then(Value::as_str)
+                                    .map(str::trim)
+                                    .filter(|value| !value.is_empty())?;
+                                let data = source
+                                    .get("data")
+                                    .and_then(Value::as_str)
+                                    .map(str::trim)
+                                    .filter(|value| !value.is_empty())?;
+                                normalized.push(ClaudeNormalizedBlock::FileData(build_data_url(
+                                    media_type, data,
+                                )));
+                            }
+                            "url" => {
+                                let url = source
+                                    .get("url")
+                                    .and_then(Value::as_str)
+                                    .map(str::trim)
+                                    .filter(|value| !value.is_empty())?
+                                    .to_string();
+                                normalized.push(ClaudeNormalizedBlock::FileUrl(url));
+                            }
+                            _ => {}
+                        }
+                    }
                     "tool_use" => {
                         let name = block
                             .get("name")
@@ -227,6 +269,216 @@ fn normalize_claude_content_blocks(content: &Value) -> Option<Vec<ClaudeNormaliz
     }
 }
 
+fn append_claude_user_message_to_openai_messages(
+    content: Option<&Value>,
+    messages: &mut Vec<Value>,
+) -> Option<()> {
+    let Some(content) = content else {
+        return Some(());
+    };
+    let mut pending_parts = Vec::new();
+    for block in normalize_claude_content_blocks(content)? {
+        match block {
+            ClaudeNormalizedBlock::Text(text) | ClaudeNormalizedBlock::Thinking { text, .. } => {
+                push_openai_text_part(&mut pending_parts, text);
+            }
+            ClaudeNormalizedBlock::RedactedThinking { .. } => {}
+            ClaudeNormalizedBlock::ImageUrl(url) => {
+                pending_parts.push(build_openai_image_part(url));
+            }
+            ClaudeNormalizedBlock::FileData(file_data) => {
+                pending_parts.push(build_openai_file_part(file_data));
+            }
+            ClaudeNormalizedBlock::FileUrl(url) => {
+                push_openai_text_part(&mut pending_parts, format!("[File: {url}]"));
+            }
+            ClaudeNormalizedBlock::ToolResult {
+                tool_use_id,
+                content,
+            } => {
+                flush_openai_user_content_parts(&mut pending_parts, messages);
+                messages.push(json!({
+                    "role": "tool",
+                    "tool_call_id": tool_use_id,
+                    "content": content,
+                }));
+            }
+            ClaudeNormalizedBlock::ToolUse { .. } => {}
+        }
+    }
+    flush_openai_user_content_parts(&mut pending_parts, messages);
+    Some(())
+}
+
+fn normalize_claude_assistant_message_to_openai_message(
+    content: Option<&Value>,
+    next_generated_tool_use_index: &mut usize,
+) -> Option<Value> {
+    let mut reasoning_segments = Vec::new();
+    let mut reasoning_parts = Vec::new();
+    let mut content_parts = Vec::new();
+    let mut tool_calls = Vec::new();
+    if let Some(content) = content {
+        for block in normalize_claude_content_blocks(content)? {
+            match block {
+                ClaudeNormalizedBlock::Text(text) => {
+                    push_openai_text_part(&mut content_parts, text);
+                }
+                ClaudeNormalizedBlock::Thinking { text, signature } => {
+                    if !text.trim().is_empty() {
+                        reasoning_segments.push(text.clone());
+                    }
+                    let mut reasoning_part = Map::new();
+                    reasoning_part
+                        .insert("type".to_string(), Value::String("thinking".to_string()));
+                    reasoning_part.insert("thinking".to_string(), Value::String(text));
+                    if let Some(signature) = signature {
+                        reasoning_part.insert("signature".to_string(), Value::String(signature));
+                    }
+                    reasoning_parts.push(Value::Object(reasoning_part));
+                }
+                ClaudeNormalizedBlock::RedactedThinking { data } => {
+                    if data.trim().is_empty() {
+                        continue;
+                    }
+                    reasoning_parts.push(json!({
+                        "type": "redacted_thinking",
+                        "data": data,
+                    }));
+                }
+                ClaudeNormalizedBlock::ImageUrl(url) => {
+                    content_parts.push(build_openai_image_part(url));
+                }
+                ClaudeNormalizedBlock::FileData(file_data) => {
+                    content_parts.push(build_openai_file_part(file_data));
+                }
+                ClaudeNormalizedBlock::FileUrl(url) => {
+                    push_openai_text_part(&mut content_parts, format!("[File: {url}]"));
+                }
+                ClaudeNormalizedBlock::ToolUse { id, name, input } => {
+                    let tool_use_id = id.unwrap_or_else(|| {
+                        let generated = format!("toolu_auto_{next_generated_tool_use_index}");
+                        *next_generated_tool_use_index += 1;
+                        generated
+                    });
+                    tool_calls.push(json!({
+                        "id": tool_use_id,
+                        "type": "function",
+                        "function": {
+                            "name": name,
+                            "arguments": canonical_json_string(input.unwrap_or(Value::Object(Map::new()))),
+                        }
+                    }));
+                }
+                ClaudeNormalizedBlock::ToolResult { .. } => {}
+            }
+        }
+    }
+    let mut assistant = Map::new();
+    assistant.insert("role".to_string(), Value::String("assistant".to_string()));
+    assistant.insert(
+        "content".to_string(),
+        match build_openai_content_value(content_parts) {
+            Some(content) => content,
+            None if !tool_calls.is_empty() => Value::Null,
+            None => Value::String(String::new()),
+        },
+    );
+    if !reasoning_segments.is_empty() {
+        assistant.insert(
+            "reasoning_content".to_string(),
+            Value::String(reasoning_segments.join("")),
+        );
+    }
+    if !reasoning_parts.is_empty() {
+        assistant.insert("reasoning_parts".to_string(), Value::Array(reasoning_parts));
+    }
+    if !tool_calls.is_empty() {
+        assistant.insert("tool_calls".to_string(), Value::Array(tool_calls));
+    }
+    Some(Value::Object(assistant))
+}
+
+fn flush_openai_user_content_parts(pending_parts: &mut Vec<Value>, messages: &mut Vec<Value>) {
+    let parts = std::mem::take(pending_parts);
+    let Some(content) = build_openai_content_value(parts) else {
+        return;
+    };
+    messages.push(json!({
+        "role": "user",
+        "content": content,
+    }));
+}
+
+fn build_openai_content_value(parts: Vec<Value>) -> Option<Value> {
+    if parts.is_empty() {
+        return None;
+    }
+    if parts
+        .iter()
+        .all(|part| part.get("type").and_then(Value::as_str) == Some("text"))
+    {
+        let text = parts
+            .iter()
+            .filter_map(|part| part.get("text").and_then(Value::as_str))
+            .collect::<Vec<_>>()
+            .join("\n\n");
+        return Some(Value::String(text));
+    }
+    Some(Value::Array(parts))
+}
+
+fn push_openai_text_part(parts: &mut Vec<Value>, text: String) {
+    if text.trim().is_empty() {
+        return;
+    }
+    parts.push(json!({
+        "type": "text",
+        "text": text,
+    }));
+}
+
+fn build_openai_image_part(url: String) -> Value {
+    json!({
+        "type": "image_url",
+        "image_url": {
+            "url": url,
+        }
+    })
+}
+
+fn build_openai_file_part(file_data: String) -> Value {
+    json!({
+        "type": "file",
+        "file": {
+            "file_data": file_data,
+        }
+    })
+}
+
+fn build_data_url(media_type: &str, data: &str) -> String {
+    format!("data:{media_type};base64,{data}")
+}
+
+fn extract_claude_output_reasoning_effort(request: &Map<String, Value>) -> Option<&'static str> {
+    match request
+        .get("output_config")
+        .and_then(Value::as_object)
+        .and_then(|config| config.get("effort"))
+        .and_then(Value::as_str)
+        .map(str::trim)
+        .filter(|value| !value.is_empty())?
+        .to_ascii_lowercase()
+        .as_str()
+    {
+        "low" => Some("low"),
+        "medium" => Some("medium"),
+        "high" => Some("high"),
+        "max" | "xhigh" => Some("xhigh"),
+        _ => None,
+    }
+}
+
 fn extract_claude_system_text(system: Option<&Value>) -> Option<String> {
     let system = system?;
     let text = match system {
@@ -326,6 +578,7 @@ fn extract_claude_web_search_options(tools: Option<&Value>) -> Option<Value> {
         if !tool_type.starts_with("web_search") {
             continue;
         }
+        let found = true;
         let mut options = Map::new();
         if let Some(max_uses) = tool.get("max_uses").and_then(Value::as_u64) {
             let search_context_size = if max_uses <= 1 {
@@ -357,7 +610,7 @@ fn extract_claude_web_search_options(tools: Option<&Value>) -> Option<Value> {
                 );
             }
         }
-        if !options.is_empty() {
+        if found {
             return Some(Value::Object(options));
         }
     }
@@ -540,4 +793,114 @@ mod tests {
         assert_eq!(normalized["parallel_tool_calls"], false);
         assert!(normalized.get("tools").is_none());
     }
+
+    #[test]
+    fn normalizes_claude_media_thinking_and_stop_sequences() {
+        let request = json!({
+            "model": "claude-sonnet-4-5",
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        { "type": "text", "text": "See attachment" },
+                        {
+                            "type": "image",
+                            "source": {
+                                "type": "url",
+                                "url": "https://example.com/cat.png"
+                            }
+                        },
+                        {
+                            "type": "document",
+                            "source": {
+                                "type": "base64",
+                                "media_type": "application/pdf",
+                                "data": "JVBERi0x"
+                            }
+                        }
+                    ]
+                },
+                {
+                    "role": "assistant",
+                    "content": [
+                        {
+                            "type": "thinking",
+                            "thinking": "need context first",
+                            "signature": "sig_123"
+                        },
+                        { "type": "redacted_thinking", "data": "redacted_blob" },
+                        { "type": "text", "text": "Working on it" }
+                    ]
+                }
+            ],
+            "stop_sequences": ["END"],
+            "output_config": { "effort": "max" }
+        });
+
+        let normalized = normalize_claude_request_to_openai_chat_request(&request)
+            .expect("request should convert");
+
+        assert_eq!(normalized["stop"], json!(["END"]));
+        assert_eq!(normalized["reasoning_effort"], "xhigh");
+        assert_eq!(
+            normalized["messages"][0]["content"],
+            json!([
+                { "type": "text", "text": "See attachment" },
+                {
+                    "type": "image_url",
+                    "image_url": { "url": "https://example.com/cat.png" }
+                },
+                {
+                    "type": "file",
+                    "file": {
+                        "file_data": "data:application/pdf;base64,JVBERi0x"
+                    }
+                }
+            ])
+        );
+        assert_eq!(
+            normalized["messages"][1]["reasoning_content"],
+            "need context first"
+        );
+        assert_eq!(
+            normalized["messages"][1]["reasoning_parts"],
+            json!([
+                {
+                    "type": "thinking",
+                    "thinking": "need context first",
+                    "signature": "sig_123"
+                },
+                {
+                    "type": "redacted_thinking",
+                    "data": "redacted_blob"
+                }
+            ])
+        );
+        assert_eq!(normalized["messages"][1]["content"], "Working on it");
+    }
+
+    #[test]
+    fn preserves_default_claude_web_search_tool_as_empty_openai_options() {
+        let request = json!({
+            "model": "claude-sonnet-4-5",
+            "tools": [
+                {
+                    "type": "web_search_20250305",
+                    "name": "web_search"
+                }
+            ],
+            "messages": [
+                {
+                    "role": "user",
+                    "content": "find something"
+                }
+            ]
+        });
+
+        let normalized = normalize_claude_request_to_openai_chat_request(&request)
+            .expect("request should convert");
+
+        assert_eq!(normalized["web_search_options"], json!({}));
+        assert!(normalized.get("tools").is_none());
+    }
 }

crates/aether-ai-pipeline/src/conversion/request/to_openai_chat/gemini.rs

@@ -3,6 +3,29 @@ use serde_json::{json, Map, Value};
 use super::shared::canonical_json_string;
 use crate::planner::openai::map_thinking_budget_to_openai_reasoning_effort;
 
+const GEMINI_MAPPED_GENERATION_CONFIG_KEYS: &[&str] = &[
+    "maxOutputTokens",
+    "max_output_tokens",
+    "temperature",
+    "topP",
+    "top_p",
+    "topK",
+    "top_k",
+    "candidateCount",
+    "candidate_count",
+    "seed",
+    "stopSequences",
+    "stop_sequences",
+    "thinkingConfig",
+    "thinking_config",
+    "responseMimeType",
+    "response_mime_type",
+    "responseSchema",
+    "response_schema",
+    "responseModalities",
+    "response_modalities",
+];
+
 pub fn normalize_gemini_request_to_openai_chat_request(
     body_json: &Value,
     request_path: &str,
@@ -45,94 +68,8 @@ pub fn normalize_gemini_request_to_openai_chat_request(
                 .to_ascii_lowercase();
             let parts = content_object.get("parts").and_then(Value::as_array)?;
             match role.as_str() {
-                "model" => {
+                "model" => messages.push(normalize_gemini_model_parts_to_openai_message(parts)?),
-                    let mut text_segments = Vec::new();
+                _ => append_gemini_user_parts_to_openai_messages(parts, &mut messages)?,
-                    let mut tool_calls = Vec::new();
-                    for (index, part) in parts.iter().enumerate() {
-                        let part = part.as_object()?;
-                        if let Some(text) = part.get("text").and_then(Value::as_str) {
-                            if !text.trim().is_empty() {
-                                text_segments.push(text.to_string());
-                            }
-                        } else if let Some(function_call) =
-                            part.get("functionCall").and_then(Value::as_object)
-                        {
-                            let name = function_call
-                                .get("name")
-                                .and_then(Value::as_str)
-                                .map(str::trim)
-                                .filter(|value| !value.is_empty())?;
-                            let id = function_call
-                                .get("id")
-                                .and_then(Value::as_str)
-                                .filter(|value| !value.is_empty())
-                                .map(ToOwned::to_owned)
-                                .unwrap_or_else(|| format!("toolu_{}_{}", name, index));
-                            tool_calls.push(json!({
-                                "id": id,
-                                "type": "function",
-                                "function": {
-                                    "name": name,
-                                    "arguments": canonical_json_string(function_call.get("args").cloned().unwrap_or(Value::Object(Map::new()))),
-                                }
-                            }));
-                        }
-                    }
-                    let mut assistant = Map::new();
-                    assistant.insert("role".to_string(), Value::String("assistant".to_string()));
-                    assistant.insert(
-                        "content".to_string(),
-                        if text_segments.is_empty() && !tool_calls.is_empty() {
-                            Value::Null
-                        } else {
-                            Value::String(text_segments.join("\n\n"))
-                        },
-                    );
-                    if !tool_calls.is_empty() {
-                        assistant.insert("tool_calls".to_string(), Value::Array(tool_calls));
-                    }
-                    messages.push(Value::Object(assistant));
-                }
-                _ => {
-                    let mut text_segments = Vec::new();
-                    for part in parts {
-                        let part = part.as_object()?;
-                        if let Some(text) = part.get("text").and_then(Value::as_str) {
-                            if !text.trim().is_empty() {
-                                text_segments.push(text.to_string());
-                            }
-                        } else if let Some(function_response) =
-                            part.get("functionResponse").and_then(Value::as_object)
-                        {
-                            let name = function_response
-                                .get("name")
-                                .and_then(Value::as_str)
-                                .unwrap_or("tool");
-                            let response_value = function_response
-                                .get("response")
-                                .cloned()
-                                .unwrap_or(Value::Object(Map::new()));
-                            let tool_call_id = function_response
-                                .get("id")
-                                .and_then(Value::as_str)
-                                .filter(|value| !value.is_empty())
-                                .map(ToOwned::to_owned)
-                                .unwrap_or_else(|| format!("toolu_{}", name));
-                            messages.push(json!({
-                                "role": "tool",
-                                "tool_call_id": tool_call_id,
-                                "content": response_value,
-                            }));
-                        }
-                    }
-                    let text = text_segments.join("\n\n");
-                    if !text.trim().is_empty() {
-                        messages.push(json!({
-                            "role": "user",
-                            "content": text,
-                        }));
-                    }
-                }
             }
         }
     }
@@ -142,32 +79,63 @@ pub fn normalize_gemini_request_to_openai_chat_request(
         .get("generationConfig")
         .or_else(|| request.get("generation_config"))
         .and_then(Value::as_object);
+    let mut google_extra = Map::new();
+    let mut gemini_extra = Map::new();
     if let Some(generation_config) = generation_config {
-        if let Some(value) = generation_config.get("maxOutputTokens").cloned() {
+        if let Some(value) =
+            generation_config_value(generation_config, "maxOutputTokens", "max_output_tokens")
+                .cloned()
+        {
             output.insert("max_completion_tokens".to_string(), value);
         }
         if let Some(value) = generation_config.get("temperature").cloned() {
             output.insert("temperature".to_string(), value);
         }
-        if let Some(value) = generation_config.get("topP").cloned() {
+        if let Some(value) = generation_config_value(generation_config, "topP", "top_p").cloned() {
             output.insert("top_p".to_string(), value);
         }
-        if let Some(value) = generation_config.get("topK").cloned() {
+        if let Some(value) = generation_config_value(generation_config, "topK", "top_k").cloned() {
             output.insert("top_k".to_string(), value);
         }
-        if let Some(value) = generation_config.get("candidateCount").cloned() {
+        if let Some(value) =
+            generation_config_value(generation_config, "candidateCount", "candidate_count").cloned()
+        {
             output.insert("n".to_string(), value);
         }
         if let Some(value) = generation_config.get("seed").cloned() {
             output.insert("seed".to_string(), value);
         }
-        if let Some(value) = generation_config.get("stopSequences").cloned() {
+        if let Some(value) =
+            generation_config_value(generation_config, "stopSequences", "stop_sequences").cloned()
+        {
             output.insert("stop".to_string(), value);
         }
-        if let Some(thinking_budget) = generation_config
+        if let Some(thinking_config) =
-            .get("thinkingConfig")
+            generation_config_value(generation_config, "thinkingConfig", "thinking_config")
                 .and_then(Value::as_object)
-            .and_then(|thinking| thinking.get("thinkingBudget"))
+        {
+            google_extra.insert(
+                "thinking_config".to_string(),
+                Value::Object(thinking_config.clone()),
+            );
+        }
+        if let Some(response_modalities) = generation_config_value(
+            generation_config,
+            "responseModalities",
+            "response_modalities",
+        )
+        .cloned()
+        {
+            google_extra.insert("response_modalities".to_string(), response_modalities);
+        }
+        if let Some(thinking_budget) =
+            generation_config_value(generation_config, "thinkingConfig", "thinking_config")
+                .and_then(Value::as_object)
+                .and_then(|thinking| {
+                    thinking
+                        .get("thinkingBudget")
+                        .or_else(|| thinking.get("thinking_budget"))
+                })
                 .and_then(Value::as_u64)
         {
             output.insert(
@@ -177,12 +145,13 @@ pub fn normalize_gemini_request_to_openai_chat_request(
                 ),
             );
         }
-        if generation_config
+        if generation_config_value(generation_config, "responseMimeType", "response_mime_type")
-            .get("responseMimeType")
             .and_then(Value::as_str)
             .is_some_and(|value| value == "application/json")
         {
-            let response_format = if let Some(schema) = generation_config.get("responseSchema") {
+            let response_format = if let Some(schema) =
+                generation_config_value(generation_config, "responseSchema", "response_schema")
+            {
                 json!({
                     "type": "json_schema",
                     "json_schema": {
@@ -195,23 +164,431 @@ pub fn normalize_gemini_request_to_openai_chat_request(
             };
             output.insert("response_format".to_string(), response_format);
         }
+
+        let mut generation_config_extra = Map::new();
+        for (key, value) in generation_config {
+            if GEMINI_MAPPED_GENERATION_CONFIG_KEYS
+                .iter()
+                .any(|candidate| candidate == &key.as_str())
+            {
+                continue;
+            }
+            generation_config_extra.insert(key.clone(), value.clone());
+        }
+        if !generation_config_extra.is_empty() {
+            gemini_extra.insert(
+                "generation_config_extra".to_string(),
+                Value::Object(generation_config_extra),
+            );
+        }
     }
     if let Some(value) = request.get("stream").cloned() {
         output.insert("stream".to_string(), value);
     }
+    if let Some(value) = request
+        .get("safetySettings")
+        .or_else(|| request.get("safety_settings"))
+        .cloned()
+    {
+        gemini_extra.insert("safety_settings".to_string(), value);
+    }
+    if let Some(value) = request
+        .get("cachedContent")
+        .or_else(|| request.get("cached_content"))
+        .cloned()
+    {
+        gemini_extra.insert("cached_content".to_string(), value);
+    }
     if let Some(tools) = normalize_gemini_tools_to_openai(request.get("tools"))? {
         output.insert("tools".to_string(), Value::Array(tools));
     }
     if let Some(web_search_options) = extract_gemini_web_search_options(request.get("tools")) {
         output.insert("web_search_options".to_string(), web_search_options);
     }
-    if let Some(tool_choice) = normalize_gemini_tool_choice_to_openai(request.get("toolConfig"))? {
+    if let Some(tool_choice) = normalize_gemini_tool_choice_to_openai(
+        request
+            .get("toolConfig")
+            .or_else(|| request.get("tool_config")),
+    )? {
         output.insert("tool_choice".to_string(), tool_choice);
     }
+    if !google_extra.is_empty() || !gemini_extra.is_empty() {
+        let mut extra_body = Map::new();
+        if !google_extra.is_empty() {
+            extra_body.insert("google".to_string(), Value::Object(google_extra));
+        }
+        if !gemini_extra.is_empty() {
+            extra_body.insert("gemini".to_string(), Value::Object(gemini_extra));
+        }
+        output.insert("extra_body".to_string(), Value::Object(extra_body));
+    }
 
     Some(Value::Object(output))
 }
 
+#[derive(Debug)]
+enum GeminiNormalizedPart {
+    Text(String),
+    Thinking {
+        text: String,
+        signature: Option<String>,
+    },
+    ImageUrl(String),
+    FileData(String),
+    FileUrl(String),
+    AudioData {
+        data: String,
+        format: String,
+    },
+    ToolUse {
+        id: Option<String>,
+        name: String,
+        input: Value,
+    },
+    ToolResult {
+        tool_use_id: String,
+        content: Value,
+    },
+}
+
+fn append_gemini_user_parts_to_openai_messages(
+    parts: &[Value],
+    messages: &mut Vec<Value>,
+) -> Option<()> {
+    let mut pending_parts = Vec::new();
+    for part in normalize_gemini_parts(parts)? {
+        match part {
+            GeminiNormalizedPart::Text(text) | GeminiNormalizedPart::Thinking { text, .. } => {
+                push_openai_text_part(&mut pending_parts, text);
+            }
+            GeminiNormalizedPart::ImageUrl(url) => {
+                pending_parts.push(build_openai_image_part(url));
+            }
+            GeminiNormalizedPart::FileData(file_data) => {
+                pending_parts.push(build_openai_file_part(file_data));
+            }
+            GeminiNormalizedPart::FileUrl(url) => {
+                push_openai_text_part(&mut pending_parts, format!("[File: {url}]"));
+            }
+            GeminiNormalizedPart::AudioData { data, format } => {
+                pending_parts.push(build_openai_audio_part(data, format));
+            }
+            GeminiNormalizedPart::ToolResult {
+                tool_use_id,
+                content,
+            } => {
+                flush_openai_user_content_parts(&mut pending_parts, messages);
+                messages.push(json!({
+                    "role": "tool",
+                    "tool_call_id": tool_use_id,
+                    "content": content,
+                }));
+            }
+            GeminiNormalizedPart::ToolUse { .. } => {}
+        }
+    }
+    flush_openai_user_content_parts(&mut pending_parts, messages);
+    Some(())
+}
+
+fn normalize_gemini_model_parts_to_openai_message(parts: &[Value]) -> Option<Value> {
+    let mut reasoning_segments = Vec::new();
+    let mut reasoning_parts = Vec::new();
+    let mut content_parts = Vec::new();
+    let mut tool_calls = Vec::new();
+    for (index, part) in normalize_gemini_parts(parts)?.into_iter().enumerate() {
+        match part {
+            GeminiNormalizedPart::Text(text) => {
+                push_openai_text_part(&mut content_parts, text);
+            }
+            GeminiNormalizedPart::Thinking { text, signature } => {
+                if !text.trim().is_empty() {
+                    reasoning_segments.push(text.clone());
+                }
+                let mut reasoning_part = Map::new();
+                reasoning_part.insert("type".to_string(), Value::String("thinking".to_string()));
+                reasoning_part.insert("thinking".to_string(), Value::String(text));
+                if let Some(signature) = signature {
+                    reasoning_part.insert("signature".to_string(), Value::String(signature));
+                }
+                reasoning_parts.push(Value::Object(reasoning_part));
+            }
+            GeminiNormalizedPart::ImageUrl(url) => {
+                content_parts.push(build_openai_image_part(url));
+            }
+            GeminiNormalizedPart::FileData(file_data) => {
+                content_parts.push(build_openai_file_part(file_data));
+            }
+            GeminiNormalizedPart::FileUrl(url) => {
+                push_openai_text_part(&mut content_parts, format!("[File: {url}]"));
+            }
+            GeminiNormalizedPart::AudioData { data, format } => {
+                content_parts.push(build_openai_audio_part(data, format));
+            }
+            GeminiNormalizedPart::ToolUse { id, name, input } => {
+                let tool_id = id.unwrap_or_else(|| format!("toolu_{}_{}", name, index));
+                tool_calls.push(json!({
+                    "id": tool_id,
+                    "type": "function",
+                    "function": {
+                        "name": name,
+                        "arguments": canonical_json_string(input),
+                    }
+                }));
+            }
+            GeminiNormalizedPart::ToolResult { .. } => {}
+        }
+    }
+
+    let mut assistant = Map::new();
+    assistant.insert("role".to_string(), Value::String("assistant".to_string()));
+    assistant.insert(
+        "content".to_string(),
+        match build_openai_content_value(content_parts) {
+            Some(content) => content,
+            None if !tool_calls.is_empty() => Value::Null,
+            None => Value::String(String::new()),
+        },
+    );
+    if !reasoning_segments.is_empty() {
+        assistant.insert(
+            "reasoning_content".to_string(),
+            Value::String(reasoning_segments.join("")),
+        );
+    }
+    if !reasoning_parts.is_empty() {
+        assistant.insert("reasoning_parts".to_string(), Value::Array(reasoning_parts));
+    }
+    if !tool_calls.is_empty() {
+        assistant.insert("tool_calls".to_string(), Value::Array(tool_calls));
+    }
+    Some(Value::Object(assistant))
+}
+
+fn normalize_gemini_parts(parts: &[Value]) -> Option<Vec<GeminiNormalizedPart>> {
+    let mut normalized = Vec::new();
+    for part in parts {
+        let part = part.as_object()?;
+        if let Some(text) = part.get("text").and_then(Value::as_str) {
+            if part
+                .get("thought")
+                .and_then(Value::as_bool)
+                .unwrap_or(false)
+            {
+                normalized.push(GeminiNormalizedPart::Thinking {
+                    text: text.to_string(),
+                    signature: part
+                        .get("thoughtSignature")
+                        .or_else(|| part.get("thought_signature"))
+                        .and_then(Value::as_str)
+                        .filter(|value| !value.is_empty())
+                        .map(ToOwned::to_owned),
+                });
+            } else {
+                normalized.push(GeminiNormalizedPart::Text(text.to_string()));
+            }
+            continue;
+        }
+        if let Some(inline_data) = part
+            .get("inlineData")
+            .or_else(|| part.get("inline_data"))
+            .and_then(Value::as_object)
+        {
+            let mime_type = inline_data
+                .get("mimeType")
+                .or_else(|| inline_data.get("mime_type"))
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            let data = inline_data
+                .get("data")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            if mime_type.starts_with("image/") {
+                normalized.push(GeminiNormalizedPart::ImageUrl(build_data_url(
+                    mime_type, data,
+                )));
+            } else if let Some(format) = mime_type.strip_prefix("audio/") {
+                normalized.push(GeminiNormalizedPart::AudioData {
+                    data: data.to_string(),
+                    format: format.to_string(),
+                });
+            } else {
+                normalized.push(GeminiNormalizedPart::FileData(build_data_url(
+                    mime_type, data,
+                )));
+            }
+            continue;
+        }
+        if let Some(file_data) = part
+            .get("fileData")
+            .or_else(|| part.get("file_data"))
+            .and_then(Value::as_object)
+        {
+            let file_uri = file_data
+                .get("fileUri")
+                .or_else(|| file_data.get("file_uri"))
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            let mime_type = file_data
+                .get("mimeType")
+                .or_else(|| file_data.get("mime_type"))
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty());
+            if mime_type.is_some_and(|value| value.starts_with("image/")) {
+                normalized.push(GeminiNormalizedPart::ImageUrl(file_uri.to_string()));
+            } else {
+                normalized.push(GeminiNormalizedPart::FileUrl(file_uri.to_string()));
+            }
+            continue;
+        }
+        if let Some(function_call) = part
+            .get("functionCall")
+            .or_else(|| part.get("function_call"))
+            .and_then(Value::as_object)
+        {
+            let name = function_call
+                .get("name")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?
+                .to_string();
+            normalized.push(GeminiNormalizedPart::ToolUse {
+                id: function_call
+                    .get("id")
+                    .and_then(Value::as_str)
+                    .filter(|value| !value.is_empty())
+                    .map(ToOwned::to_owned),
+                name,
+                input: function_call
+                    .get("args")
+                    .cloned()
+                    .unwrap_or_else(|| Value::Object(Map::new())),
+            });
+            continue;
+        }
+        if let Some(function_response) = part
+            .get("functionResponse")
+            .or_else(|| part.get("function_response"))
+            .and_then(Value::as_object)
+        {
+            let tool_use_id = function_response
+                .get("id")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())
+                .map(ToOwned::to_owned)
+                .or_else(|| {
+                    function_response
+                        .get("name")
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .filter(|value| !value.is_empty())
+                        .map(ToOwned::to_owned)
+                })?;
+            let response_value = function_response
+                .get("response")
+                .cloned()
+                .unwrap_or_else(|| Value::Object(Map::new()));
+            let content = match response_value {
+                Value::Object(mut object) => object
+                    .remove("result")
+                    .unwrap_or_else(|| Value::Object(object)),
+                other => other,
+            };
+            normalized.push(GeminiNormalizedPart::ToolResult {
+                tool_use_id,
+                content,
+            });
+        }
+    }
+    Some(normalized)
+}
+
+fn flush_openai_user_content_parts(pending_parts: &mut Vec<Value>, messages: &mut Vec<Value>) {
+    let parts = std::mem::take(pending_parts);
+    let Some(content) = build_openai_content_value(parts) else {
+        return;
+    };
+    messages.push(json!({
+        "role": "user",
+        "content": content,
+    }));
+}
+
+fn build_openai_content_value(parts: Vec<Value>) -> Option<Value> {
+    if parts.is_empty() {
+        return None;
+    }
+    if parts
+        .iter()
+        .all(|part| part.get("type").and_then(Value::as_str) == Some("text"))
+    {
+        let text = parts
+            .iter()
+            .filter_map(|part| part.get("text").and_then(Value::as_str))
+            .collect::<Vec<_>>()
+            .join("\n\n");
+        return Some(Value::String(text));
+    }
+    Some(Value::Array(parts))
+}
+
+fn push_openai_text_part(parts: &mut Vec<Value>, text: String) {
+    if text.trim().is_empty() {
+        return;
+    }
+    parts.push(json!({
+        "type": "text",
+        "text": text,
+    }));
+}
+
+fn build_openai_image_part(url: String) -> Value {
+    json!({
+        "type": "image_url",
+        "image_url": {
+            "url": url,
+        }
+    })
+}
+
+fn build_openai_file_part(file_data: String) -> Value {
+    json!({
+        "type": "file",
+        "file": {
+            "file_data": file_data,
+        }
+    })
+}
+
+fn build_openai_audio_part(data: String, format: String) -> Value {
+    json!({
+        "type": "input_audio",
+        "input_audio": {
+            "data": data,
+            "format": format,
+        }
+    })
+}
+
+fn build_data_url(mime_type: &str, data: &str) -> String {
+    format!("data:{mime_type};base64,{data}")
+}
+
+fn generation_config_value<'a>(
+    generation_config: &'a Map<String, Value>,
+    camel: &str,
+    snake: &str,
+) -> Option<&'a Value> {
+    generation_config
+        .get(camel)
+        .or_else(|| generation_config.get(snake))
+}
+
 fn extract_gemini_system_text(system_instruction: Option<&Value>) -> Option<String> {
     let system_instruction = system_instruction?;
     match system_instruction {
@@ -458,4 +835,128 @@ mod tests {
             ])
         );
     }
+
+    #[test]
+    fn normalizes_gemini_multimodal_thought_and_passthrough_config() {
+        let request = json!({
+            "contents": [
+                {
+                    "role": "user",
+                    "parts": [
+                        { "text": "Look at these" },
+                        { "inlineData": { "mimeType": "image/png", "data": "iVBORw0KGgo=" } },
+                        { "inline_data": { "mime_type": "application/pdf", "data": "JVBERi0x" } },
+                        { "inlineData": { "mimeType": "audio/mp3", "data": "SUQz" } },
+                        {
+                            "functionResponse": {
+                                "name": "lookup",
+                                "id": "call_1",
+                                "response": { "result": { "city": "Shanghai" } }
+                            }
+                        }
+                    ]
+                },
+                {
+                    "role": "model",
+                    "parts": [
+                        { "text": "reasoning", "thought": true, "thoughtSignature": "sig_123" },
+                        { "text": "done" },
+                        { "fileData": { "fileUri": "https://example.com/cat.png", "mimeType": "image/png" } },
+                        { "fileData": { "fileUri": "https://example.com/report.pdf", "mimeType": "application/pdf" } },
+                        {
+                            "functionCall": {
+                                "name": "lookup",
+                                "id": "call_1",
+                                "args": { "city": "Shanghai" }
+                            }
+                        }
+                    ]
+                }
+            ],
+            "generation_config": {
+                "max_output_tokens": 128,
+                "stop_sequences": ["END"],
+                "thinking_config": {
+                    "includeThoughts": true,
+                    "thinkingBudget": 4096
+                },
+                "responseModalities": ["TEXT", "IMAGE"],
+                "candidate_count": 2,
+                "presencePenalty": 0.5
+            },
+            "safetySettings": [{ "category": "HARM_CATEGORY_HATE_SPEECH" }],
+            "cachedContent": "cached/123"
+        });
+
+        let normalized = normalize_gemini_request_to_openai_chat_request(
+            &request,
+            "/v1beta/models/gemini-2.5-pro:generateContent",
+        )
+        .expect("request should convert");
+
+        assert_eq!(normalized["model"], "gemini-2.5-pro");
+        assert_eq!(
+            normalized["messages"][2]["reasoning_parts"],
+            json!([
+                {
+                    "type": "thinking",
+                    "thinking": "reasoning",
+                    "signature": "sig_123"
+                }
+            ])
+        );
+        assert_eq!(
+            normalized["messages"][0]["content"],
+            json!([
+                { "type": "text", "text": "Look at these" },
+                {
+                    "type": "image_url",
+                    "image_url": { "url": "data:image/png;base64,iVBORw0KGgo=" }
+                },
+                {
+                    "type": "file",
+                    "file": { "file_data": "data:application/pdf;base64,JVBERi0x" }
+                },
+                {
+                    "type": "input_audio",
+                    "input_audio": { "data": "SUQz", "format": "mp3" }
+                }
+            ])
+        );
+        assert_eq!(normalized["messages"][1]["role"], "tool");
+        assert_eq!(normalized["messages"][1]["tool_call_id"], "call_1");
+        assert_eq!(
+            normalized["messages"][1]["content"],
+            json!({ "city": "Shanghai" })
+        );
+        assert_eq!(normalized["messages"][2]["reasoning_content"], "reasoning");
+        assert_eq!(
+            normalized["messages"][2]["content"],
+            json!([
+                { "type": "text", "text": "done" },
+                {
+                    "type": "image_url",
+                    "image_url": { "url": "https://example.com/cat.png" }
+                },
+                { "type": "text", "text": "[File: https://example.com/report.pdf]" }
+            ])
+        );
+        assert_eq!(normalized["messages"][2]["tool_calls"][0]["id"], "call_1");
+        assert_eq!(normalized["max_completion_tokens"], 128);
+        assert_eq!(normalized["n"], 2);
+        assert_eq!(normalized["stop"], json!(["END"]));
+        assert_eq!(normalized["reasoning_effort"], "high");
+        assert_eq!(
+            normalized["extra_body"]["google"]["response_modalities"],
+            json!(["TEXT", "IMAGE"])
+        );
+        assert_eq!(
+            normalized["extra_body"]["gemini"]["generation_config_extra"]["presencePenalty"],
+            0.5
+        );
+        assert_eq!(
+            normalized["extra_body"]["gemini"]["cached_content"],
+            "cached/123"
+        );
+    }
 }

crates/aether-ai-pipeline/src/conversion/response/from_openai_chat/claude_chat.rs

@@ -1,8 +1,6 @@
 use serde_json::{json, Value};
 
-use super::shared::{
+use super::shared::{build_generated_tool_call_id, parse_openai_function_arguments};
-    build_generated_tool_call_id, extract_openai_assistant_text, parse_openai_function_arguments,
-};
 
 pub fn convert_openai_chat_response_to_claude_chat(
     body_json: &Value,
@@ -12,24 +10,10 @@ pub fn convert_openai_chat_response_to_claude_chat(
     let choices = body.get("choices")?.as_array()?;
     let first_choice = choices.first()?.as_object()?;
     let message = first_choice.get("message")?.as_object()?;
-    let mut content = Vec::new();
+    let mut content = extract_openai_reasoning_to_claude_blocks(message);
-
+    content.extend(convert_openai_assistant_content_to_claude_blocks(
-    if let Some(reasoning_content) = message.get("reasoning_content").and_then(Value::as_str) {
+        message.get("content"),
-        if !reasoning_content.trim().is_empty() {
+    )?);
-            content.push(json!({
-                "type": "thinking",
-                "thinking": reasoning_content,
-            }));
-        }
-    }
-    if let Some(text) = extract_openai_assistant_text(message.get("content")) {
-        if !text.trim().is_empty() {
-            content.push(json!({
-                "type": "text",
-                "text": text,
-            }));
-        }
-    }
     if let Some(tool_call_values) = message.get("tool_calls").and_then(Value::as_array) {
         for (index, tool_call) in tool_call_values.iter().enumerate() {
             let tool_call = tool_call.as_object()?;
@@ -121,6 +105,225 @@ pub fn convert_openai_chat_response_to_claude_chat(
     })
 }
 
+fn extract_openai_reasoning_to_claude_blocks(
+    message: &serde_json::Map<String, Value>,
+) -> Vec<Value> {
+    let mut blocks = Vec::new();
+    if let Some(reasoning_parts) = message.get("reasoning_parts").and_then(Value::as_array) {
+        for reasoning_part in reasoning_parts {
+            let Some(reasoning_object) = reasoning_part.as_object() else {
+                continue;
+            };
+            match reasoning_object
+                .get("type")
+                .and_then(Value::as_str)
+                .unwrap_or("thinking")
+            {
+                "thinking" => {
+                    let thinking = reasoning_object
+                        .get("thinking")
+                        .or_else(|| reasoning_object.get("text"))
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .unwrap_or_default();
+                    if thinking.is_empty() {
+                        continue;
+                    }
+                    let mut block = serde_json::Map::new();
+                    block.insert("type".to_string(), Value::String("thinking".to_string()));
+                    block.insert("thinking".to_string(), Value::String(thinking.to_string()));
+                    if let Some(signature) = reasoning_object
+                        .get("signature")
+                        .and_then(Value::as_str)
+                        .filter(|value| !value.is_empty())
+                    {
+                        block.insert(
+                            "signature".to_string(),
+                            Value::String(signature.to_string()),
+                        );
+                    }
+                    blocks.push(Value::Object(block));
+                }
+                "redacted_thinking" => {
+                    let data = reasoning_object
+                        .get("data")
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .unwrap_or_default();
+                    if !data.is_empty() {
+                        blocks.push(json!({
+                            "type": "redacted_thinking",
+                            "data": data,
+                        }));
+                    }
+                }
+                _ => {}
+            }
+        }
+    }
+    if !blocks.is_empty() {
+        return blocks;
+    }
+    if let Some(reasoning_content) = message
+        .get("reasoning_content")
+        .and_then(Value::as_str)
+        .map(str::trim)
+        .filter(|value| !value.is_empty())
+    {
+        blocks.push(json!({
+            "type": "thinking",
+            "thinking": reasoning_content,
+        }));
+    }
+    blocks
+}
+
+fn convert_openai_assistant_content_to_claude_blocks(
+    content: Option<&Value>,
+) -> Option<Vec<Value>> {
+    match content {
+        None | Some(Value::Null) => Some(Vec::new()),
+        Some(Value::String(text)) => {
+            if text.trim().is_empty() {
+                Some(Vec::new())
+            } else {
+                Some(vec![json!({
+                    "type": "text",
+                    "text": text,
+                })])
+            }
+        }
+        Some(Value::Array(parts)) => {
+            let mut blocks = Vec::new();
+            for part in parts {
+                let part = part.as_object()?;
+                let part_type = part
+                    .get("type")
+                    .and_then(Value::as_str)
+                    .unwrap_or_default()
+                    .trim()
+                    .to_ascii_lowercase();
+                match part_type.as_str() {
+                    "text" | "output_text" => {
+                        if let Some(text) = part.get("text").and_then(Value::as_str) {
+                            if !text.trim().is_empty() {
+                                blocks.push(json!({
+                                    "type": "text",
+                                    "text": text,
+                                }));
+                            }
+                        }
+                    }
+                    "image_url" | "output_image" => {
+                        if let Some(url) = extract_openai_image_url(part) {
+                            if let Some((media_type, data)) = parse_data_url(url.as_str()) {
+                                blocks.push(json!({
+                                    "type": "image",
+                                    "source": {
+                                        "type": "base64",
+                                        "media_type": media_type,
+                                        "data": data,
+                                    }
+                                }));
+                            } else {
+                                blocks.push(json!({
+                                    "type": "image",
+                                    "source": {
+                                        "type": "url",
+                                        "url": url,
+                                    }
+                                }));
+                            }
+                        }
+                    }
+                    "file" => {
+                        let file = part.get("file").and_then(Value::as_object).unwrap_or(part);
+                        if let Some(file_data) = file.get("file_data").and_then(Value::as_str) {
+                            if let Some((media_type, data)) = parse_data_url(file_data) {
+                                blocks.push(json!({
+                                    "type": "document",
+                                    "source": {
+                                        "type": "base64",
+                                        "media_type": media_type,
+                                        "data": data,
+                                    }
+                                }));
+                            }
+                        } else if let Some(file_id) = file
+                            .get("file_id")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty())
+                        {
+                            blocks.push(json!({
+                                "type": "text",
+                                "text": format!("[File: {file_id}]"),
+                            }));
+                        }
+                    }
+                    "input_audio" => {
+                        let audio = part
+                            .get("input_audio")
+                            .and_then(Value::as_object)
+                            .unwrap_or(part);
+                        let data = audio
+                            .get("data")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty());
+                        let format = audio
+                            .get("format")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty());
+                        if let (Some(data), Some(format)) = (data, format) {
+                            blocks.push(json!({
+                                "type": "document",
+                                "source": {
+                                    "type": "base64",
+                                    "media_type": format!("audio/{format}"),
+                                    "data": data,
+                                }
+                            }));
+                        }
+                    }
+                    _ => {}
+                }
+            }
+            Some(blocks)
+        }
+        _ => None,
+    }
+}
+
+fn extract_openai_image_url(part: &serde_json::Map<String, Value>) -> Option<String> {
+    part.get("image_url")
+        .and_then(|value| {
+            value.as_str().map(ToOwned::to_owned).or_else(|| {
+                value
+                    .as_object()
+                    .and_then(|object| object.get("url"))
+                    .and_then(Value::as_str)
+                    .map(ToOwned::to_owned)
+            })
+        })
+        .or_else(|| {
+            part.get("url")
+                .and_then(Value::as_str)
+                .map(ToOwned::to_owned)
+        })
+}
+
+fn parse_data_url(value: &str) -> Option<(String, String)> {
+    let rest = value.strip_prefix("data:")?;
+    let (meta, data) = rest.split_once(",")?;
+    let media_type = meta.strip_suffix(";base64")?;
+    if media_type.trim().is_empty() || data.trim().is_empty() {
+        return None;
+    }
+    Some((media_type.to_string(), data.to_string()))
+}
+
 #[cfg(test)]
 mod tests {
     use super::convert_openai_chat_response_to_claude_chat;
@@ -136,7 +339,18 @@ mod tests {
                 "message": {
                     "role": "assistant",
                     "content": "hello",
-                    "reasoning_content": "step by step"
+                    "reasoning_content": "step by step",
+                    "reasoning_parts": [
+                        {
+                            "type": "thinking",
+                            "thinking": "step by step",
+                            "signature": "sig_123"
+                        },
+                        {
+                            "type": "redacted_thinking",
+                            "data": "redacted_blob"
+                        }
+                    ]
                 },
                 "finish_reason": "stop"
             }],
@@ -155,7 +369,51 @@ mod tests {
 
         assert_eq!(converted["content"][0]["type"], "thinking");
         assert_eq!(converted["content"][0]["thinking"], "step by step");
+        assert_eq!(converted["content"][0]["signature"], "sig_123");
+        assert_eq!(converted["content"][1]["type"], "redacted_thinking");
         assert_eq!(converted["usage"]["cache_read_input_tokens"], 3);
         assert_eq!(converted["usage"]["cache_creation_input_tokens"], 2);
     }
+
+    #[test]
+    fn converts_openai_multipart_content_into_claude_blocks() {
+        let response = json!({
+            "id": "chatcmpl_img_123",
+            "model": "gpt-5.4",
+            "choices": [{
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": [
+                        { "type": "text", "text": "See attached." },
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": "data:image/png;base64,iVBORw0KGgo="
+                            }
+                        },
+                        {
+                            "type": "file",
+                            "file": {
+                                "file_data": "data:application/pdf;base64,JVBERi0x"
+                            }
+                        }
+                    ]
+                },
+                "finish_reason": "stop"
+            }]
+        });
+
+        let converted = convert_openai_chat_response_to_claude_chat(&response, &json!({}))
+            .expect("response should convert");
+
+        assert_eq!(converted["content"][0]["type"], "text");
+        assert_eq!(converted["content"][1]["type"], "image");
+        assert_eq!(converted["content"][1]["source"]["media_type"], "image/png");
+        assert_eq!(converted["content"][2]["type"], "document");
+        assert_eq!(
+            converted["content"][2]["source"]["media_type"],
+            "application/pdf"
+        );
+    }
 }

crates/aether-ai-pipeline/src/conversion/response/from_openai_chat/gemini_chat.rs

@@ -1,8 +1,6 @@
 use serde_json::{json, Value};
 
-use super::shared::{
+use super::shared::{build_generated_tool_call_id, parse_openai_function_arguments};
-    build_generated_tool_call_id, extract_openai_assistant_text, parse_openai_function_arguments,
-};
 
 pub fn convert_openai_chat_response_to_gemini_chat(
     body_json: &Value,
@@ -14,21 +12,10 @@ pub fn convert_openai_chat_response_to_gemini_chat(
     for choice in choices {
         let choice = choice.as_object()?;
         let message = choice.get("message")?.as_object()?;
-        let mut parts = Vec::new();
+        let mut parts = extract_openai_reasoning_to_gemini_parts(message);
-
+        parts.extend(convert_openai_assistant_content_to_gemini_parts(
-        if let Some(reasoning_content) = message.get("reasoning_content").and_then(Value::as_str) {
+            message.get("content"),
-            if !reasoning_content.trim().is_empty() {
+        )?);
-                parts.push(json!({
-                    "text": reasoning_content,
-                    "thought": true,
-                }));
-            }
-        }
-        if let Some(text) = extract_openai_assistant_text(message.get("content")) {
-            if !text.trim().is_empty() {
-                parts.push(json!({ "text": text }));
-            }
-        }
         if let Some(tool_call_values) = message.get("tool_calls").and_then(Value::as_array) {
             for (index, tool_call) in tool_call_values.iter().enumerate() {
                 let tool_call = tool_call.as_object()?;
@@ -120,6 +107,214 @@ pub fn convert_openai_chat_response_to_gemini_chat(
     }))
 }
 
+fn extract_openai_reasoning_to_gemini_parts(
+    message: &serde_json::Map<String, Value>,
+) -> Vec<Value> {
+    let mut parts = Vec::new();
+    if let Some(reasoning_parts) = message.get("reasoning_parts").and_then(Value::as_array) {
+        for reasoning_part in reasoning_parts {
+            let Some(reasoning_object) = reasoning_part.as_object() else {
+                continue;
+            };
+            if reasoning_object
+                .get("type")
+                .and_then(Value::as_str)
+                .is_some_and(|value| value != "thinking")
+            {
+                continue;
+            }
+            let thinking = reasoning_object
+                .get("thinking")
+                .or_else(|| reasoning_object.get("text"))
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .unwrap_or_default();
+            if thinking.is_empty() {
+                continue;
+            }
+            let mut part = serde_json::Map::new();
+            part.insert("text".to_string(), Value::String(thinking.to_string()));
+            part.insert("thought".to_string(), Value::Bool(true));
+            if let Some(signature) = reasoning_object
+                .get("signature")
+                .and_then(Value::as_str)
+                .filter(|value| !value.is_empty())
+            {
+                part.insert(
+                    "thoughtSignature".to_string(),
+                    Value::String(signature.to_string()),
+                );
+            }
+            parts.push(Value::Object(part));
+        }
+    }
+    if !parts.is_empty() {
+        return parts;
+    }
+    if let Some(reasoning_content) = message
+        .get("reasoning_content")
+        .and_then(Value::as_str)
+        .map(str::trim)
+        .filter(|value| !value.is_empty())
+    {
+        parts.push(json!({
+            "text": reasoning_content,
+            "thought": true,
+        }));
+    }
+    parts
+}
+
+fn convert_openai_assistant_content_to_gemini_parts(content: Option<&Value>) -> Option<Vec<Value>> {
+    match content {
+        None | Some(Value::Null) => Some(Vec::new()),
+        Some(Value::String(text)) => {
+            if text.trim().is_empty() {
+                Some(Vec::new())
+            } else {
+                Some(vec![json!({ "text": text })])
+            }
+        }
+        Some(Value::Array(parts)) => {
+            let mut converted = Vec::new();
+            for part in parts {
+                let part = part.as_object()?;
+                let part_type = part
+                    .get("type")
+                    .and_then(Value::as_str)
+                    .unwrap_or_default()
+                    .trim()
+                    .to_ascii_lowercase();
+                match part_type.as_str() {
+                    "text" | "output_text" => {
+                        if let Some(text) = part.get("text").and_then(Value::as_str) {
+                            if !text.trim().is_empty() {
+                                converted.push(json!({ "text": text }));
+                            }
+                        }
+                    }
+                    "image_url" | "output_image" => {
+                        let image_url = part
+                            .get("image_url")
+                            .and_then(|value| {
+                                value.as_str().map(ToOwned::to_owned).or_else(|| {
+                                    value
+                                        .as_object()
+                                        .and_then(|object| object.get("url"))
+                                        .and_then(Value::as_str)
+                                        .map(ToOwned::to_owned)
+                                })
+                            })
+                            .or_else(|| {
+                                part.get("url")
+                                    .and_then(Value::as_str)
+                                    .map(ToOwned::to_owned)
+                            })?;
+                        if let Some((mime_type, data)) = parse_data_url(image_url.as_str()) {
+                            converted.push(json!({
+                                "inlineData": {
+                                    "mimeType": mime_type,
+                                    "data": data,
+                                }
+                            }));
+                        } else {
+                            converted.push(json!({
+                                "fileData": {
+                                    "fileUri": image_url,
+                                    "mimeType": guess_media_type_from_reference(image_url.as_str(), "image/jpeg"),
+                                }
+                            }));
+                        }
+                    }
+                    "file" | "input_file" => {
+                        let file_object =
+                            part.get("file").and_then(Value::as_object).unwrap_or(part);
+                        if let Some(file_data) =
+                            file_object.get("file_data").and_then(Value::as_str)
+                        {
+                            if let Some((mime_type, data)) = parse_data_url(file_data) {
+                                converted.push(json!({
+                                    "inlineData": {
+                                        "mimeType": mime_type,
+                                        "data": data,
+                                    }
+                                }));
+                            }
+                        } else if let Some(file_id) = file_object
+                            .get("file_id")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty())
+                        {
+                            converted.push(json!({
+                                "text": format!("[File: {file_id}]"),
+                            }));
+                        }
+                    }
+                    "input_audio" => {
+                        let audio_object = part
+                            .get("input_audio")
+                            .and_then(Value::as_object)
+                            .unwrap_or(part);
+                        let data = audio_object
+                            .get("data")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty());
+                        let format = audio_object
+                            .get("format")
+                            .and_then(Value::as_str)
+                            .map(str::trim)
+                            .filter(|value| !value.is_empty());
+                        if let (Some(data), Some(format)) = (data, format) {
+                            converted.push(json!({
+                                "inlineData": {
+                                    "mimeType": format!("audio/{format}"),
+                                    "data": data,
+                                }
+                            }));
+                        }
+                    }
+                    _ => {}
+                }
+            }
+            Some(converted)
+        }
+        _ => None,
+    }
+}
+
+fn parse_data_url(value: &str) -> Option<(String, String)> {
+    let rest = value.strip_prefix("data:")?;
+    let (meta, data) = rest.split_once(",")?;
+    let mime_type = meta.strip_suffix(";base64")?;
+    if mime_type.trim().is_empty() || data.trim().is_empty() {
+        return None;
+    }
+    Some((mime_type.to_string(), data.to_string()))
+}
+
+fn guess_media_type_from_reference(reference: &str, default_mime: &str) -> String {
+    let normalized = reference
+        .split('?')
+        .next()
+        .unwrap_or(reference)
+        .to_ascii_lowercase();
+    if normalized.ends_with(".png") {
+        "image/png".to_string()
+    } else if normalized.ends_with(".gif") {
+        "image/gif".to_string()
+    } else if normalized.ends_with(".webp") {
+        "image/webp".to_string()
+    } else if normalized.ends_with(".jpg") || normalized.ends_with(".jpeg") {
+        "image/jpeg".to_string()
+    } else if normalized.ends_with(".pdf") {
+        "application/pdf".to_string()
+    } else {
+        default_mime.to_string()
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::convert_openai_chat_response_to_gemini_chat;
@@ -136,7 +331,14 @@ mod tests {
                     "message": {
                         "role": "assistant",
                         "content": "hello",
-                        "reasoning_content": "step by step"
+                        "reasoning_content": "step by step",
+                        "reasoning_parts": [
+                            {
+                                "type": "thinking",
+                                "thinking": "step by step",
+                                "signature": "sig_123"
+                            }
+                        ]
                     },
                     "finish_reason": "stop"
                 },
@@ -181,6 +383,10 @@ mod tests {
             converted["candidates"][0]["content"]["parts"][0]["thought"],
             true
         );
+        assert_eq!(
+            converted["candidates"][0]["content"]["parts"][0]["thoughtSignature"],
+            "sig_123"
+        );
         assert_eq!(
             converted["candidates"][1]["content"]["parts"][0]["functionCall"]["name"],
             "lookup"
@@ -188,4 +394,97 @@ mod tests {
         assert_eq!(converted["usageMetadata"]["candidatesTokenCount"], 5);
         assert_eq!(converted["usageMetadata"]["thoughtsTokenCount"], 2);
     }
+
+    #[test]
+    fn preserves_multimodal_openai_content_in_gemini_response() {
+        let response = json!({
+            "id": "chatcmpl_mm_123",
+            "model": "gpt-5.4",
+            "choices": [{
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "reasoning_content": "step by step",
+                    "content": [
+                        { "type": "text", "text": "Attached." },
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": "data:image/png;base64,iVBORw0KGgo="
+                            }
+                        },
+                        {
+                            "type": "file",
+                            "file": {
+                                "file_data": "data:application/pdf;base64,JVBERi0x"
+                            }
+                        },
+                        {
+                            "type": "input_audio",
+                            "input_audio": {
+                                "data": "SUQz",
+                                "format": "mp3"
+                            }
+                        },
+                        {
+                            "type": "file",
+                            "file": { "file_id": "file_123" }
+                        }
+                    ]
+                },
+                "finish_reason": "stop"
+            }],
+            "usage": {
+                "prompt_tokens": 4,
+                "completion_tokens": 3,
+                "completion_tokens_details": { "reasoning_tokens": 1 },
+                "total_tokens": 7
+            }
+        });
+
+        let converted = convert_openai_chat_response_to_gemini_chat(&response, &json!({}))
+            .expect("response should convert");
+
+        assert_eq!(
+            converted["candidates"][0]["content"]["parts"][0]["thought"],
+            true
+        );
+        assert_eq!(
+            converted["candidates"][0]["content"]["parts"][1],
+            json!({ "text": "Attached." })
+        );
+        assert_eq!(
+            converted["candidates"][0]["content"]["parts"][2],
+            json!({
+                "inlineData": {
+                    "mimeType": "image/png",
+                    "data": "iVBORw0KGgo="
+                }
+            })
+        );
+        assert_eq!(
+            converted["candidates"][0]["content"]["parts"][3],
+            json!({
+                "inlineData": {
+                    "mimeType": "application/pdf",
+                    "data": "JVBERi0x"
+                }
+            })
+        );
+        assert_eq!(
+            converted["candidates"][0]["content"]["parts"][4],
+            json!({
+                "inlineData": {
+                    "mimeType": "audio/mp3",
+                    "data": "SUQz"
+                }
+            })
+        );
+        assert_eq!(
+            converted["candidates"][0]["content"]["parts"][5],
+            json!({ "text": "[File: file_123]" })
+        );
+        assert_eq!(converted["usageMetadata"]["candidatesTokenCount"], 2);
+        assert_eq!(converted["usageMetadata"]["thoughtsTokenCount"], 1);
+    }
 }

crates/aether-ai-pipeline/src/conversion/response/from_openai_chat/openai_cli.rs

@@ -97,6 +97,14 @@ pub fn convert_openai_chat_response_to_openai_cli(
                         }
                         message_content.push(image_part);
                     }
+                } else if matches!(part_type.as_str(), "file" | "input_file") {
+                    if let Some(file_part) = build_openai_cli_file_part(part) {
+                        message_content.push(file_part);
+                    }
+                } else if part_type == "input_audio" {
+                    if let Some(audio_part) = build_openai_cli_input_audio_part(part) {
+                        message_content.push(audio_part);
+                    }
                 }
             }
         }
@@ -238,6 +246,49 @@ pub fn convert_openai_chat_response_to_openai_cli(
     Some(response)
 }
 
+fn build_openai_cli_file_part(part: &serde_json::Map<String, Value>) -> Option<Value> {
+    let file_object = part.get("file").and_then(Value::as_object).unwrap_or(part);
+    let mut file = serde_json::Map::new();
+    for key in ["file_data", "file_id", "filename"] {
+        if let Some(value) = file_object
+            .get(key)
+            .cloned()
+            .filter(|value| !value.is_null())
+        {
+            file.insert(key.to_string(), value);
+        }
+    }
+    if file.is_empty() {
+        return None;
+    }
+    Some(json!({
+        "type": "file",
+        "file": Value::Object(file),
+    }))
+}
+
+fn build_openai_cli_input_audio_part(part: &serde_json::Map<String, Value>) -> Option<Value> {
+    let audio_object = part
+        .get("input_audio")
+        .and_then(Value::as_object)
+        .unwrap_or(part);
+    let data = audio_object
+        .get("data")
+        .cloned()
+        .filter(|value| value.as_str().is_some_and(|value| !value.trim().is_empty()))?;
+    let format = audio_object
+        .get("format")
+        .cloned()
+        .filter(|value| value.as_str().is_some_and(|value| !value.trim().is_empty()))?;
+    Some(json!({
+        "type": "input_audio",
+        "input_audio": {
+            "data": data,
+            "format": format,
+        }
+    }))
+}
+
 #[cfg(test)]
 mod tests {
     use super::convert_openai_chat_response_to_openai_cli;
@@ -321,4 +372,70 @@ mod tests {
             json!({"reasoning_tokens": 0})
         );
     }
+
+    #[test]
+    fn preserves_file_and_audio_parts_when_converting_to_responses() {
+        let response = json!({
+            "id": "chatcmpl_mm_123",
+            "object": "chat.completion",
+            "model": "gpt-5",
+            "choices": [{
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": [
+                        { "type": "text", "text": "Attached." },
+                        {
+                            "type": "file",
+                            "file": {
+                                "file_data": "data:application/pdf;base64,JVBERi0x",
+                                "filename": "report.pdf"
+                            }
+                        },
+                        {
+                            "type": "input_audio",
+                            "input_audio": {
+                                "data": "SUQz",
+                                "format": "mp3"
+                            }
+                        }
+                    ]
+                },
+                "finish_reason": "stop"
+            }],
+            "usage": {
+                "prompt_tokens": 4,
+                "completion_tokens": 2,
+                "total_tokens": 6
+            }
+        });
+
+        let converted = convert_openai_chat_response_to_openai_cli(&response, &json!({}), false)
+            .expect("chat response should convert to responses");
+
+        assert_eq!(
+            converted["output"][0]["content"],
+            json!([
+                {
+                    "type": "output_text",
+                    "text": "Attached.",
+                    "annotations": []
+                },
+                {
+                    "type": "file",
+                    "file": {
+                        "file_data": "data:application/pdf;base64,JVBERi0x",
+                        "filename": "report.pdf"
+                    }
+                },
+                {
+                    "type": "input_audio",
+                    "input_audio": {
+                        "data": "SUQz",
+                        "format": "mp3"
+                    }
+                }
+            ])
+        );
+    }
 }

crates/aether-ai-pipeline/src/conversion/response/from_openai_chat/shared.rs

@@ -114,38 +114,22 @@ pub fn build_openai_cli_response_with_content(
     })
 }
 
-pub(super) fn extract_openai_assistant_text(content: Option<&Value>) -> Option<String> {
-    match content? {
-        Value::Null => Some(String::new()),
-        Value::String(text) => Some(text.clone()),
-        Value::Array(parts) => {
-            let mut text = String::new();
-            for part in parts {
-                let part = part.as_object()?;
-                let part_type = part
-                    .get("type")
-                    .and_then(Value::as_str)
-                    .unwrap_or_default()
-                    .trim()
-                    .to_ascii_lowercase();
-                if matches!(part_type.as_str(), "text" | "output_text") {
-                    if let Some(piece) = part.get("text").and_then(Value::as_str) {
-                        text.push_str(piece);
-                    }
-                }
-            }
-            Some(text)
-        }
-        _ => None,
-    }
-}
-
 pub(super) fn parse_openai_function_arguments(arguments: Option<&Value>) -> Option<Value> {
     match arguments.cloned().unwrap_or(Value::Object(Map::new())) {
-        Value::String(text) => serde_json::from_str(&text)
+        Value::Object(object) => Some(Value::Object(object)),
-            .ok()
+        Value::String(text) => {
-            .or(Some(Value::String(text))),
+            let trimmed = text.trim();
-        other => Some(other),
+            if trimmed.is_empty() {
+                Some(Value::Object(Map::new()))
+            } else {
+                match serde_json::from_str::<Value>(trimmed) {
+                    Ok(Value::Object(object)) => Some(Value::Object(object)),
+                    Ok(other) => Some(json!({ "raw": other })),
+                    Err(_) => Some(json!({ "raw": text })),
+                }
+            }
+        }
+        other => Some(json!({ "raw": other })),
     }
 }
 

crates/aether-ai-pipeline/src/conversion/response/to_openai_chat/claude_chat.rs

@@ -9,22 +9,53 @@ pub fn convert_claude_chat_response_to_openai_chat(
     let body = body_json.as_object()?;
     let content = body.get("content")?.as_array()?;
     let mut text = String::new();
+    let mut content_parts = Vec::new();
     let mut reasoning_content = String::new();
+    let mut reasoning_parts = Vec::new();
     let mut tool_calls = Vec::new();
+    let mut has_non_text_content = false;
     for (index, block) in content.iter().enumerate() {
         let block = block.as_object()?;
         match block.get("type")?.as_str()? {
             "text" => {
-                text.push_str(block.get("text")?.as_str()?);
+                let piece = block.get("text")?.as_str()?;
+                push_openai_text_part(&mut text, &mut content_parts, piece);
             }
             "thinking" => {
-                if let Some(piece) = block
+                let piece = block
                     .get("thinking")
                     .and_then(Value::as_str)
                     .or_else(|| block.get("text").and_then(Value::as_str))
-                {
+                    .unwrap_or_default();
+                if !piece.is_empty() {
                     reasoning_content.push_str(piece);
                 }
+                let mut reasoning_part = Map::new();
+                reasoning_part.insert("type".to_string(), Value::String("thinking".to_string()));
+                reasoning_part.insert("thinking".to_string(), Value::String(piece.to_string()));
+                if let Some(signature) = block
+                    .get("signature")
+                    .and_then(Value::as_str)
+                    .filter(|value| !value.is_empty())
+                {
+                    reasoning_part.insert(
+                        "signature".to_string(),
+                        Value::String(signature.to_string()),
+                    );
+                }
+                reasoning_parts.push(Value::Object(reasoning_part));
+            }
+            "redacted_thinking" => {
+                let data = block
+                    .get("data")
+                    .and_then(Value::as_str)
+                    .unwrap_or_default();
+                if !data.is_empty() {
+                    reasoning_parts.push(json!({
+                        "type": "redacted_thinking",
+                        "data": data,
+                    }));
+                }
             }
             "tool_use" => {
                 let tool_name = block.get("name")?.as_str()?;
@@ -44,6 +75,21 @@ pub fn convert_claude_chat_response_to_openai_chat(
                     }
                 }));
             }
+            "image" => {
+                content_parts.push(convert_claude_image_block_to_openai_part(block)?);
+                has_non_text_content = true;
+            }
+            "document" => {
+                let part = convert_claude_document_block_to_openai_part(block)?;
+                if part.get("type").and_then(Value::as_str) == Some("text") {
+                    if let Some(piece) = part.get("text").and_then(Value::as_str) {
+                        push_openai_text_part(&mut text, &mut content_parts, piece);
+                    }
+                } else {
+                    content_parts.push(part);
+                    has_non_text_content = true;
+                }
+            }
             _ => continue,
         }
     }
@@ -77,8 +123,10 @@ pub fn convert_claude_chat_response_to_openai_chat(
         .get("id")
         .and_then(Value::as_str)
         .unwrap_or("chatcmpl-local-finalize");
-    let message_content = if text.is_empty() && !tool_calls.is_empty() {
+    let message_content = if content_parts.is_empty() && !tool_calls.is_empty() {
         Value::Null
+    } else if has_non_text_content {
+        Value::Array(content_parts)
     } else {
         Value::String(text)
     };
@@ -91,6 +139,9 @@ pub fn convert_claude_chat_response_to_openai_chat(
             Value::String(reasoning_content),
         );
     }
+    if !reasoning_parts.is_empty() {
+        message.insert("reasoning_parts".to_string(), Value::Array(reasoning_parts));
+    }
     if !tool_calls.is_empty() {
         message.insert("tool_calls".to_string(), Value::Array(tool_calls));
     }
@@ -141,6 +192,108 @@ pub fn convert_claude_chat_response_to_openai_chat(
     })
 }
 
+fn push_openai_text_part(text: &mut String, content_parts: &mut Vec<Value>, piece: &str) {
+    if piece.is_empty() {
+        return;
+    }
+    text.push_str(piece);
+    content_parts.push(json!({
+        "type": "text",
+        "text": piece,
+    }));
+}
+
+fn convert_claude_image_block_to_openai_part(
+    block: &serde_json::Map<String, Value>,
+) -> Option<Value> {
+    let source = block.get("source")?.as_object()?;
+    match source.get("type")?.as_str()? {
+        "base64" => {
+            let media_type = source
+                .get("media_type")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            let data = source
+                .get("data")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            Some(json!({
+                "type": "image_url",
+                "image_url": {
+                    "url": build_data_url(media_type, data),
+                }
+            }))
+        }
+        "url" => {
+            let url = source
+                .get("url")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            Some(json!({
+                "type": "image_url",
+                "image_url": {
+                    "url": url,
+                }
+            }))
+        }
+        _ => None,
+    }
+}
+
+fn convert_claude_document_block_to_openai_part(
+    block: &serde_json::Map<String, Value>,
+) -> Option<Value> {
+    let source = block.get("source")?.as_object()?;
+    match source.get("type")?.as_str()? {
+        "base64" => {
+            let media_type = source
+                .get("media_type")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            let data = source
+                .get("data")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            if let Some(format) = media_type.strip_prefix("audio/") {
+                return Some(json!({
+                    "type": "input_audio",
+                    "input_audio": {
+                        "data": data,
+                        "format": format,
+                    }
+                }));
+            }
+            Some(json!({
+                "type": "file",
+                "file": {
+                    "file_data": build_data_url(media_type, data),
+                }
+            }))
+        }
+        "url" => {
+            let url = source
+                .get("url")
+                .and_then(Value::as_str)
+                .map(str::trim)
+                .filter(|value| !value.is_empty())?;
+            Some(json!({
+                "type": "text",
+                "text": format!("[File: {url}]"),
+            }))
+        }
+        _ => None,
+    }
+}
+
+fn build_data_url(media_type: &str, data: &str) -> String {
+    format!("data:{media_type};base64,{data}")
+}
+
 #[cfg(test)]
 mod tests {
     use super::convert_claude_chat_response_to_openai_chat;
@@ -152,7 +305,7 @@ mod tests {
             "id": "msg_123",
             "model": "claude-sonnet-4-5",
             "content": [
-                { "type": "thinking", "thinking": "step by step" },
+                { "type": "thinking", "thinking": "step by step", "signature": "sig_123" },
                 { "type": "text", "text": "hello" }
             ],
             "stop_reason": "end_turn",
@@ -176,6 +329,16 @@ mod tests {
             converted["choices"][0]["message"]["reasoning_content"],
             "step by step"
         );
+        assert_eq!(
+            converted["choices"][0]["message"]["reasoning_parts"],
+            json!([
+                {
+                    "type": "thinking",
+                    "thinking": "step by step",
+                    "signature": "sig_123"
+                }
+            ])
+        );
         assert_eq!(
             converted["usage"]["prompt_tokens_details"]["cached_tokens"],
             3
@@ -186,4 +349,88 @@ mod tests {
         );
         assert_eq!(converted["service_tier"], "default");
     }
+
+    #[test]
+    fn converts_claude_multimodal_content_into_openai_chat_parts() {
+        let response = json!({
+            "id": "msg_multimodal_123",
+            "model": "claude-sonnet-4-5",
+            "content": [
+                { "type": "thinking", "thinking": "step by step" },
+                { "type": "text", "text": "See attached." },
+                {
+                    "type": "image",
+                    "source": {
+                        "type": "url",
+                        "url": "https://example.com/cat.png"
+                    }
+                },
+                {
+                    "type": "document",
+                    "source": {
+                        "type": "base64",
+                        "media_type": "application/pdf",
+                        "data": "JVBERi0x"
+                    }
+                },
+                {
+                    "type": "document",
+                    "source": {
+                        "type": "base64",
+                        "media_type": "audio/mp3",
+                        "data": "SUQz"
+                    }
+                },
+                {
+                    "type": "tool_use",
+                    "id": "call_1",
+                    "name": "lookup",
+                    "input": { "city": "Shanghai" }
+                }
+            ],
+            "stop_reason": "tool_use",
+            "usage": {
+                "input_tokens": 9,
+                "output_tokens": 4
+            }
+        });
+
+        let converted = convert_claude_chat_response_to_openai_chat(&response, &json!({}))
+            .expect("response should convert");
+
+        assert_eq!(
+            converted["choices"][0]["message"]["reasoning_content"],
+            "step by step"
+        );
+        assert_eq!(
+            converted["choices"][0]["message"]["content"],
+            json!([
+                { "type": "text", "text": "See attached." },
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": "https://example.com/cat.png"
+                    }
+                },
+                {
+                    "type": "file",
+                    "file": {
+                        "file_data": "data:application/pdf;base64,JVBERi0x"
+                    }
+                },
+                {
+                    "type": "input_audio",
+                    "input_audio": {
+                        "data": "SUQz",
+                        "format": "mp3"
+                    }
+                }
+            ])
+        );
+        assert_eq!(converted["choices"][0]["finish_reason"], "tool_calls");
+        assert_eq!(
+            converted["choices"][0]["message"]["tool_calls"][0]["function"]["arguments"],
+            "{\"city\":\"Shanghai\"}"
+        );
+    }
 }

crates/aether-ai-pipeline/src/conversion/response/to_openai_chat/claude_cli.rs

@@ -1,87 +1,12 @@
-use serde_json::{json, Value};
+use serde_json::Value;
 
-use super::super::from_openai_chat::{
+use super::super::from_openai_chat::convert_openai_chat_response_to_openai_cli;
-    build_openai_cli_response_with_reasoning, OpenAiCliResponseUsage,
+use super::claude_chat::convert_claude_chat_response_to_openai_chat;
-};
-use super::shared::{build_generated_tool_call_id, canonicalize_tool_arguments};
 
 pub fn convert_claude_cli_response_to_openai_cli(
     body_json: &Value,
     report_context: &Value,
 ) -> Option<Value> {
-    let body = body_json.as_object()?;
+    let canonical = convert_claude_chat_response_to_openai_chat(body_json, report_context)?;
-    let content = body.get("content")?.as_array()?;
+    convert_openai_chat_response_to_openai_cli(&canonical, report_context, false)
-    let mut text = String::new();
-    let mut reasoning_summaries = Vec::new();
-    let mut function_calls = Vec::new();
-    for (index, block) in content.iter().enumerate() {
-        let block = block.as_object()?;
-        match block.get("type")?.as_str()? {
-            "text" => {
-                text.push_str(block.get("text")?.as_str()?);
-            }
-            "thinking" => {
-                if let Some(piece) = block
-                    .get("thinking")
-                    .and_then(Value::as_str)
-                    .or_else(|| block.get("text").and_then(Value::as_str))
-                {
-                    if !piece.trim().is_empty() {
-                        reasoning_summaries.push(piece.to_string());
-                    }
-                }
-            }
-            "tool_use" => {
-                let tool_name = block.get("name")?.as_str()?;
-                let call_id = block
-                    .get("id")
-                    .and_then(Value::as_str)
-                    .filter(|value| !value.is_empty())
-                    .map(ToOwned::to_owned)
-                    .unwrap_or_else(|| build_generated_tool_call_id(index));
-                let arguments = canonicalize_tool_arguments(block.get("input").cloned());
-                function_calls.push(json!({
-                    "type": "function_call",
-                    "call_id": call_id,
-                    "name": tool_name,
-                    "arguments": arguments,
-                }));
-            }
-            _ => continue,
-        }
-    }
-
-    let usage = body.get("usage").and_then(Value::as_object);
-    let prompt_tokens = usage
-        .and_then(|value| value.get("input_tokens"))
-        .and_then(Value::as_u64)
-        .unwrap_or(0);
-    let output_tokens = usage
-        .and_then(|value| value.get("output_tokens"))
-        .and_then(Value::as_u64)
-        .unwrap_or(0);
-    let total_tokens = prompt_tokens + output_tokens;
-    let model = body
-        .get("model")
-        .and_then(Value::as_str)
-        .or_else(|| report_context.get("mapped_model").and_then(Value::as_str))
-        .or_else(|| report_context.get("model").and_then(Value::as_str))
-        .unwrap_or("unknown");
-    let response_id = body
-        .get("id")
-        .and_then(Value::as_str)
-        .unwrap_or("resp-local-finalize");
-
-    Some(build_openai_cli_response_with_reasoning(
-        response_id,
-        model,
-        &text,
-        reasoning_summaries,
-        function_calls,
-        OpenAiCliResponseUsage {
-            prompt_tokens,
-            output_tokens,
-            total_tokens,
-        },
-    ))
 }

crates/aether-ai-pipeline/src/conversion/response/to_openai_chat/gemini_chat.rs

@@ -18,6 +18,7 @@ pub fn convert_gemini_chat_response_to_openai_chat(
         let mut text = String::new();
         let mut content_parts = Vec::new();
         let mut reasoning_content = String::new();
+        let mut reasoning_parts = Vec::new();
         let mut tool_calls = Vec::new();
         let mut has_non_text_content = false;
         for (index, part) in parts.iter().enumerate() {
@@ -29,6 +30,22 @@ pub fn convert_gemini_chat_response_to_openai_chat(
                     .unwrap_or(false)
                 {
                     reasoning_content.push_str(piece);
+                    let mut reasoning_part = Map::new();
+                    reasoning_part
+                        .insert("type".to_string(), Value::String("thinking".to_string()));
+                    reasoning_part.insert("thinking".to_string(), Value::String(piece.to_string()));
+                    if let Some(signature) = part
+                        .get("thoughtSignature")
+                        .or_else(|| part.get("thought_signature"))
+                        .and_then(Value::as_str)
+                        .filter(|value| !value.is_empty())
+                    {
+                        reasoning_part.insert(
+                            "signature".to_string(),
+                            Value::String(signature.to_string()),
+                        );
+                    }
+                    reasoning_parts.push(Value::Object(reasoning_part));
                 } else {
                     text.push_str(piece);
                     content_parts.push(json!({
@@ -60,14 +77,15 @@ pub fn convert_gemini_chat_response_to_openai_chat(
                     "type": "text",
                     "text": rendered_text,
                 }));
-            } else if let Some(image_url) = extract_gemini_image_url(part) {
+            } else if let Some(content_part) = convert_gemini_part_to_openai_content_part(part) {
-                content_parts.push(json!({
+                if content_part.get("type").and_then(Value::as_str) == Some("text") {
-                    "type": "image_url",
+                    if let Some(piece) = content_part.get("text").and_then(Value::as_str) {
-                    "image_url": {
+                        text.push_str(piece);
-                        "url": image_url,
                     }
-                }));
+                } else {
                     has_non_text_content = true;
+                }
+                content_parts.push(content_part);
             } else {
                 continue;
             }
@@ -100,6 +118,9 @@ pub fn convert_gemini_chat_response_to_openai_chat(
                 Value::String(reasoning_content),
             );
         }
+        if !reasoning_parts.is_empty() {
+            message.insert("reasoning_parts".to_string(), Value::Array(reasoning_parts));
+        }
         if !tool_calls.is_empty() {
             message.insert("tool_calls".to_string(), Value::Array(tool_calls));
         }
@@ -177,6 +198,69 @@ fn render_gemini_textual_part(part: &Map<String, Value>) -> Option<String> {
     None
 }
 
+fn convert_gemini_part_to_openai_content_part(part: &Map<String, Value>) -> Option<Value> {
+    if let Some(image_url) = extract_gemini_image_url(part) {
+        return Some(json!({
+            "type": "image_url",
+            "image_url": {
+                "url": image_url,
+            }
+        }));
+    }
+
+    if let Some(inline_data) = part
+        .get("inlineData")
+        .or_else(|| part.get("inline_data"))
+        .and_then(Value::as_object)
+    {
+        let mime_type = inline_data
+            .get("mimeType")
+            .or_else(|| inline_data.get("mime_type"))
+            .and_then(Value::as_str)
+            .map(str::trim)
+            .filter(|value| !value.is_empty())?;
+        let data = inline_data
+            .get("data")
+            .and_then(Value::as_str)
+            .map(str::trim)
+            .filter(|value| !value.is_empty())?;
+        if let Some(format) = mime_type.strip_prefix("audio/") {
+            return Some(json!({
+                "type": "input_audio",
+                "input_audio": {
+                    "data": data,
+                    "format": format,
+                }
+            }));
+        }
+        return Some(json!({
+            "type": "file",
+            "file": {
+                "file_data": format!("data:{mime_type};base64,{data}"),
+            }
+        }));
+    }
+
+    if let Some(file_data) = part
+        .get("fileData")
+        .or_else(|| part.get("file_data"))
+        .and_then(Value::as_object)
+    {
+        let file_uri = file_data
+            .get("fileUri")
+            .or_else(|| file_data.get("file_uri"))
+            .and_then(Value::as_str)
+            .map(str::trim)
+            .filter(|value| !value.is_empty())?;
+        return Some(json!({
+            "type": "text",
+            "text": format!("[File: {file_uri}]"),
+        }));
+    }
+
+    None
+}
+
 #[cfg(test)]
 mod tests {
     use super::convert_gemini_chat_response_to_openai_chat;
@@ -193,7 +277,7 @@ mod tests {
                     "finishReason": "RECITATION",
                     "content": {
                         "parts": [
-                            { "text": "thinking", "thought": true },
+                            { "text": "thinking", "thought": true, "thoughtSignature": "sig_123" },
                             { "executableCode": { "language": "python", "code": "print(1)" } },
                             { "codeExecutionResult": { "output": "1" } }
                         ]
@@ -226,6 +310,16 @@ mod tests {
             converted["choices"][0]["message"]["reasoning_content"],
             "thinking"
         );
+        assert_eq!(
+            converted["choices"][0]["message"]["reasoning_parts"],
+            json!([
+                {
+                    "type": "thinking",
+                    "thinking": "thinking",
+                    "signature": "sig_123"
+                }
+            ])
+        );
         let content = converted["choices"][0]["message"]["content"]
             .as_str()
             .expect("content should be string");
@@ -238,4 +332,53 @@ mod tests {
         );
         assert_eq!(converted["usage"]["completion_tokens"], 7);
     }
+
+    #[test]
+    fn preserves_gemini_multimodal_parts_in_openai_chat_response() {
+        let response = json!({
+            "responseId": "resp_mm_123",
+            "modelVersion": "gemini-2.5-pro",
+            "candidates": [{
+                "index": 0,
+                "finishReason": "STOP",
+                "content": {
+                    "parts": [
+                        { "text": "Attached." },
+                        { "inlineData": { "mimeType": "image/png", "data": "iVBORw0KGgo=" } },
+                        { "inlineData": { "mimeType": "application/pdf", "data": "JVBERi0x" } },
+                        { "inline_data": { "mime_type": "audio/mp3", "data": "SUQz" } },
+                        { "fileData": { "fileUri": "https://example.com/report.pdf", "mimeType": "application/pdf" } }
+                    ]
+                }
+            }],
+            "usageMetadata": {
+                "promptTokenCount": 4,
+                "candidatesTokenCount": 2,
+                "totalTokenCount": 6
+            }
+        });
+
+        let converted = convert_gemini_chat_response_to_openai_chat(&response, &json!({}))
+            .expect("response should convert");
+
+        assert_eq!(
+            converted["choices"][0]["message"]["content"],
+            json!([
+                { "type": "text", "text": "Attached." },
+                {
+                    "type": "image_url",
+                    "image_url": { "url": "data:image/png;base64,iVBORw0KGgo=" }
+                },
+                {
+                    "type": "file",
+                    "file": { "file_data": "data:application/pdf;base64,JVBERi0x" }
+                },
+                {
+                    "type": "input_audio",
+                    "input_audio": { "data": "SUQz", "format": "mp3" }
+                },
+                { "type": "text", "text": "[File: https://example.com/report.pdf]" }
+            ])
+        );
+    }
 }

crates/aether-ai-pipeline/src/conversion/response/to_openai_chat/gemini_cli.rs

@@ -1,110 +1,12 @@
-use serde_json::{json, Value};
+use serde_json::Value;
 
-use super::super::from_openai_chat::{
+use super::super::from_openai_chat::convert_openai_chat_response_to_openai_cli;
-    build_openai_cli_response_with_content, OpenAiCliResponseUsage,
+use super::gemini_chat::convert_gemini_chat_response_to_openai_chat;
-};
-use super::shared::{
-    build_generated_tool_call_id, canonicalize_tool_arguments, extract_gemini_image_url,
-};
 
 pub fn convert_gemini_cli_response_to_openai_cli(
     body_json: &Value,
     report_context: &Value,
 ) -> Option<Value> {
-    let body = body_json.as_object()?;
+    let canonical = convert_gemini_chat_response_to_openai_chat(body_json, report_context)?;
-    let candidates = body.get("candidates")?.as_array()?;
+    convert_openai_chat_response_to_openai_cli(&canonical, report_context, false)
-    let first_candidate = candidates.first()?.as_object()?;
-    let content = first_candidate.get("content")?.as_object()?;
-    let parts = content.get("parts")?.as_array()?;
-    let mut message_content = Vec::new();
-    let mut reasoning_summaries = Vec::new();
-    let mut function_calls = Vec::new();
-    for (index, part) in parts.iter().enumerate() {
-        let part = part.as_object()?;
-        if let Some(piece) = part.get("text").and_then(Value::as_str) {
-            if part
-                .get("thought")
-                .and_then(Value::as_bool)
-                .unwrap_or(false)
-            {
-                if !piece.trim().is_empty() {
-                    reasoning_summaries.push(piece.to_string());
-                }
-            } else {
-                message_content.push(json!({
-                    "type": "output_text",
-                    "text": piece,
-                    "annotations": []
-                }));
-            }
-        } else if let Some(function_call) = part.get("functionCall").and_then(Value::as_object) {
-            let tool_name = function_call.get("name")?.as_str()?;
-            let call_id = function_call
-                .get("id")
-                .and_then(Value::as_str)
-                .filter(|value| !value.is_empty())
-                .map(ToOwned::to_owned)
-                .unwrap_or_else(|| build_generated_tool_call_id(index));
-            let arguments = canonicalize_tool_arguments(function_call.get("args").cloned());
-            function_calls.push(json!({
-                "type": "function_call",
-                "call_id": call_id,
-                "name": tool_name,
-                "arguments": arguments,
-            }));
-        } else if let Some(image_url) = extract_gemini_image_url(part) {
-            message_content.push(json!({
-                "type": "output_image",
-                "image_url": image_url,
-            }));
-        } else {
-            continue;
-        }
-    }
-
-    let usage = body.get("usageMetadata").and_then(Value::as_object);
-    let prompt_tokens = usage
-        .and_then(|value| value.get("promptTokenCount"))
-        .and_then(Value::as_u64)
-        .unwrap_or(0);
-    let output_tokens = usage
-        .map(|value| {
-            value
-                .get("candidatesTokenCount")
-                .and_then(Value::as_u64)
-                .unwrap_or(0)
-                + value
-                    .get("thoughtsTokenCount")
-                    .and_then(Value::as_u64)
-                    .unwrap_or(0)
-        })
-        .unwrap_or(0);
-    let total_tokens = usage
-        .and_then(|value| value.get("totalTokenCount"))
-        .and_then(Value::as_u64)
-        .unwrap_or(prompt_tokens + output_tokens);
-    let model = body
-        .get("modelVersion")
-        .and_then(Value::as_str)
-        .or_else(|| report_context.get("mapped_model").and_then(Value::as_str))
-        .or_else(|| report_context.get("model").and_then(Value::as_str))
-        .unwrap_or("unknown");
-    let response_id = body
-        .get("responseId")
-        .or_else(|| body.get("_v1internal_response_id"))
-        .and_then(Value::as_str)
-        .unwrap_or("resp-local-finalize");
-
-    Some(build_openai_cli_response_with_content(
-        response_id,
-        model,
-        message_content,
-        reasoning_summaries,
-        function_calls,
-        OpenAiCliResponseUsage {
-            prompt_tokens,
-            output_tokens,
-            total_tokens,
-        },
-    ))
 }

crates/aether-ai-pipeline/src/conversion/response/to_openai_chat/openai_cli.rs

@@ -80,6 +80,18 @@ pub fn convert_openai_cli_response_to_openai_chat(
                                     }));
                                     has_non_text_content = true;
                                 }
+                            } else if part_type == "file" {
+                                if let Some(file_part) = extract_openai_response_file(part_object) {
+                                    content_parts.push(file_part);
+                                    has_non_text_content = true;
+                                }
+                            } else if part_type == "input_audio" {
+                                if let Some(audio_part) =
+                                    extract_openai_response_input_audio(part_object)
+                                {
+                                    content_parts.push(audio_part);
+                                    has_non_text_content = true;
+                                }
                             }
                         }
                     }
@@ -298,6 +310,52 @@ fn extract_openai_response_image(
     Some((image_url, detail))
 }
 
+fn extract_openai_response_file(part_object: &Map<String, Value>) -> Option<Value> {
+    let file_object = part_object
+        .get("file")
+        .and_then(Value::as_object)
+        .unwrap_or(part_object);
+    let mut file = Map::new();
+    for key in ["file_data", "file_id", "filename"] {
+        if let Some(value) = file_object
+            .get(key)
+            .cloned()
+            .filter(|value| !value.is_null())
+        {
+            file.insert(key.to_string(), value);
+        }
+    }
+    if file.is_empty() {
+        return None;
+    }
+    Some(json!({
+        "type": "file",
+        "file": Value::Object(file),
+    }))
+}
+
+fn extract_openai_response_input_audio(part_object: &Map<String, Value>) -> Option<Value> {
+    let audio_object = part_object
+        .get("input_audio")
+        .and_then(Value::as_object)
+        .unwrap_or(part_object);
+    let data = audio_object
+        .get("data")
+        .cloned()
+        .filter(|value| value.as_str().is_some_and(|value| !value.trim().is_empty()))?;
+    let format = audio_object
+        .get("format")
+        .cloned()
+        .filter(|value| value.as_str().is_some_and(|value| !value.trim().is_empty()))?;
+    Some(json!({
+        "type": "input_audio",
+        "input_audio": {
+            "data": data,
+            "format": format,
+        }
+    }))
+}
+
 fn offset_annotation_indices(annotation: &Value, offset: i64) -> Value {
     let Some(object) = annotation.as_object() else {
         return annotation.clone();
@@ -374,4 +432,63 @@ mod tests {
             json!({"reasoning_tokens": 1})
         );
     }
+
+    #[test]
+    fn preserves_file_and_audio_parts_when_converting_to_chat() {
+        let response = json!({
+            "id": "resp_mm_123",
+            "object": "response",
+            "model": "gpt-5",
+            "output": [{
+                "type": "message",
+                "role": "assistant",
+                "content": [
+                    { "type": "output_text", "text": "Attached." },
+                    {
+                        "type": "file",
+                        "file": {
+                            "file_data": "data:application/pdf;base64,JVBERi0x",
+                            "filename": "report.pdf"
+                        }
+                    },
+                    {
+                        "type": "input_audio",
+                        "input_audio": {
+                            "data": "SUQz",
+                            "format": "mp3"
+                        }
+                    }
+                ]
+            }],
+            "usage": {
+                "input_tokens": 4,
+                "output_tokens": 2,
+                "total_tokens": 6
+            }
+        });
+
+        let converted = convert_openai_cli_response_to_openai_chat(&response, &json!({}))
+            .expect("responses response should convert to chat");
+
+        assert_eq!(
+            converted["choices"][0]["message"]["content"],
+            json!([
+                { "type": "text", "text": "Attached." },
+                {
+                    "type": "file",
+                    "file": {
+                        "file_data": "data:application/pdf;base64,JVBERi0x",
+                        "filename": "report.pdf"
+                    }
+                },
+                {
+                    "type": "input_audio",
+                    "input_audio": {
+                        "data": "SUQz",
+                        "format": "mp3"
+                    }
+                }
+            ])
+        );
+    }
 }

crates/aether-ai-pipeline/src/conversion/response/to_openai_chat/shared.rs

@@ -13,17 +13,28 @@ pub(super) fn canonicalize_tool_arguments(value: Option<Value>) -> String {
 }
 
 pub(super) fn extract_gemini_image_url(part: &Map<String, Value>) -> Option<String> {
-    if let Some(inline_data) = part.get("inlineData").and_then(Value::as_object) {
+    if let Some(inline_data) = part
-        let mime_type = inline_data.get("mimeType").and_then(Value::as_str)?;
+        .get("inlineData")
+        .or_else(|| part.get("inline_data"))
+        .and_then(Value::as_object)
+    {
+        let mime_type = inline_data
+            .get("mimeType")
+            .or_else(|| inline_data.get("mime_type"))
+            .and_then(Value::as_str)?;
         if !mime_type.starts_with("image/") {
             return None;
         }
         let data = inline_data.get("data").and_then(Value::as_str)?;
         return Some(format!("data:{mime_type};base64,{data}"));
     }
-    let file_data = part.get("fileData").and_then(Value::as_object)?;
+    let file_data = part
+        .get("fileData")
+        .or_else(|| part.get("file_data"))
+        .and_then(Value::as_object)?;
     if file_data
         .get("mimeType")
+        .or_else(|| file_data.get("mime_type"))
         .and_then(Value::as_str)
         .is_some_and(|mime_type| !mime_type.starts_with("image/"))
     {
@@ -31,6 +42,7 @@ pub(super) fn extract_gemini_image_url(part: &Map<String, Value>) -> Option<Stri
     }
     file_data
         .get("fileUri")
+        .or_else(|| file_data.get("file_uri"))
         .and_then(Value::as_str)
         .map(ToOwned::to_owned)
 }

crates/aether-ai-pipeline/src/finalize/standard/claude/stream.rs

@@ -164,6 +164,21 @@ impl ClaudeProviderState {
                             event: CanonicalStreamEvent::ReasoningDelta(piece.to_string()),
                         });
                     }
+                    "signature_delta" => {
+                        let Some(signature) = delta.get("signature").and_then(Value::as_str) else {
+                            return Ok(out);
+                        };
+                        if signature.is_empty() {
+                            return Ok(out);
+                        }
+                        self.ensure_started(report_context, &mut out);
+                        let (id, model) = self.identity(report_context);
+                        out.push(CanonicalStreamFrame {
+                            id,
+                            model,
+                            event: CanonicalStreamEvent::ReasoningSignature(signature.to_string()),
+                        });
+                    }
                     _ => {}
                 }
             }
@@ -217,6 +232,16 @@ impl ClaudeProviderState {
                     });
                     return Ok(out);
                 }
+                if let Some(part) = canonical_content_part_from_claude_block(block) {
+                    self.ensure_started(report_context, &mut out);
+                    let (id, model) = self.identity(report_context);
+                    out.push(CanonicalStreamFrame {
+                        id,
+                        model,
+                        event: CanonicalStreamEvent::ContentPart(part),
+                    });
+                    return Ok(out);
+                }
                 if block_type != "tool_use" {
                     return Ok(out);
                 }
@@ -526,6 +551,27 @@ impl ClaudeClientEmitter {
                 )?);
                 Ok(out)
             }
+            CanonicalStreamEvent::ReasoningSignature(signature) => {
+                let mut out = self.ensure_started()?;
+                out.extend(self.ensure_thinking_block()?);
+                let block_index = match self.open_block {
+                    Some(ClaudeOpenBlock::Thinking { block_index }) => block_index,
+                    _ => return Ok(out),
+                };
+                out.extend(encode_json_sse(
+                    Some("content_block_delta"),
+                    &json!({
+                        "type": "content_block_delta",
+                        "index": block_index,
+                        "delta": {
+                            "type": "signature_delta",
+                            "signature": signature,
+                        }
+                    }),
+                )?);
+                Ok(out)
+            }
+            CanonicalStreamEvent::ContentPart(part) => self.emit_content_part(part),
             CanonicalStreamEvent::ToolCallStart {
                 index,
                 call_id,
@@ -632,6 +678,190 @@ impl ClaudeClientEmitter {
             },
         })
     }
+
+    fn emit_content_part(
+        &mut self,
+        part: CanonicalContentPart,
+    ) -> Result<Vec<u8>, PipelineFinalizeError> {
+        let mut out = self.ensure_started()?;
+        out.extend(self.close_open_block()?);
+        let block_index = self.next_block_index;
+        self.next_block_index += 1;
+        let content_block = match part {
+            CanonicalContentPart::ImageUrl(url) => {
+                if let Some((media_type, data)) = parse_data_url(url.as_str()) {
+                    json!({
+                        "type": "image",
+                        "source": {
+                            "type": "base64",
+                            "media_type": media_type,
+                            "data": data,
+                        }
+                    })
+                } else {
+                    json!({
+                        "type": "image",
+                        "source": {
+                            "type": "url",
+                            "url": url,
+                        }
+                    })
+                }
+            }
+            CanonicalContentPart::File {
+                file_data,
+                reference,
+                mime_type: _,
+                filename: _,
+            } => {
+                if let Some(file_data) = file_data {
+                    if let Some((media_type, data)) = parse_data_url(file_data.as_str()) {
+                        json!({
+                            "type": "document",
+                            "source": {
+                                "type": "base64",
+                                "media_type": media_type,
+                                "data": data,
+                            }
+                        })
+                    } else {
+                        json!({
+                            "type": "text",
+                            "text": "[File]",
+                        })
+                    }
+                } else if let Some(reference) = reference {
+                    json!({
+                        "type": "document",
+                        "source": {
+                            "type": "url",
+                            "url": reference,
+                        }
+                    })
+                } else {
+                    json!({
+                        "type": "text",
+                        "text": "[File]",
+                    })
+                }
+            }
+            CanonicalContentPart::Audio { data, format } => json!({
+                "type": "document",
+                "source": {
+                    "type": "base64",
+                    "media_type": format!("audio/{format}"),
+                    "data": data,
+                }
+            }),
+        };
+        out.extend(encode_json_sse(
+            Some("content_block_start"),
+            &json!({
+                "type": "content_block_start",
+                "index": block_index,
+                "content_block": content_block,
+            }),
+        )?);
+        out.extend(encode_json_sse(
+            Some("content_block_stop"),
+            &json!({
+                "type": "content_block_stop",
+                "index": block_index,
+            }),
+        )?);
+        Ok(out)
+    }
+}
+
+fn canonical_content_part_from_claude_block(
+    block: &Map<String, Value>,
+) -> Option<CanonicalContentPart> {
+    match block
+        .get("type")
+        .and_then(Value::as_str)
+        .unwrap_or_default()
+    {
+        "image" => {
+            let source = block.get("source")?.as_object()?;
+            match source.get("type")?.as_str()? {
+                "base64" => {
+                    let media_type = source
+                        .get("media_type")
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .filter(|value| !value.is_empty())?;
+                    let data = source
+                        .get("data")
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .filter(|value| !value.is_empty())?;
+                    Some(CanonicalContentPart::ImageUrl(format!(
+                        "data:{media_type};base64,{data}"
+                    )))
+                }
+                "url" => source
+                    .get("url")
+                    .and_then(Value::as_str)
+                    .map(str::trim)
+                    .filter(|value| !value.is_empty())
+                    .map(|value| CanonicalContentPart::ImageUrl(value.to_string())),
+                _ => None,
+            }
+        }
+        "document" => {
+            let source = block.get("source")?.as_object()?;
+            match source.get("type")?.as_str()? {
+                "base64" => {
+                    let media_type = source
+                        .get("media_type")
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .filter(|value| !value.is_empty())?;
+                    let data = source
+                        .get("data")
+                        .and_then(Value::as_str)
+                        .map(str::trim)
+                        .filter(|value| !value.is_empty())?;
+                    if let Some(format) = media_type.strip_prefix("audio/") {
+                        Some(CanonicalContentPart::Audio {
+                            data: data.to_string(),
+                            format: format.to_string(),
+                        })
+                    } else {
+                        Some(CanonicalContentPart::File {
+                            file_data: Some(format!("data:{media_type};base64,{data}")),
+                            reference: None,
+                            mime_type: Some(media_type.to_string()),
+                            filename: None,
+                        })
+                    }
+                }
+                "url" => source
+                    .get("url")
+                    .and_then(Value::as_str)
+                    .map(str::trim)
+                    .filter(|value| !value.is_empty())
+                    .map(|value| CanonicalContentPart::File {
+                        file_data: None,
+                        reference: Some(value.to_string()),
+                        mime_type: None,
+                        filename: None,
+                    }),
+                _ => None,
+            }
+        }
+        _ => None,
+    }
+}
+
+fn parse_data_url(value: &str) -> Option<(String, String)> {
+    let rest = value.strip_prefix("data:")?;
+    let (meta, data) = rest.split_once(',')?;
+    let media_type = meta.strip_suffix(";base64")?;
+    if media_type.trim().is_empty() || data.trim().is_empty() {
+        return None;
+    }
+    Some((media_type.to_string(), data.to_string()))
 }
 
 #[cfg(test)]
@@ -679,6 +909,42 @@ mod tests {
         )));
     }
 
+    #[test]
+    fn claude_provider_state_parses_signature_deltas() {
+        let mut state = ClaudeProviderState::default();
+        let report_context = json!({});
+        let _ = state
+            .push_line(
+                &report_context,
+                data_line(json!({
+                    "type": "message_start",
+                    "message": {
+                        "id": "msg_123",
+                        "model": "claude-sonnet-4-5"
+                    }
+                })),
+            )
+            .expect("message_start should parse");
+        let frames = state
+            .push_line(
+                &report_context,
+                data_line(json!({
+                    "type": "content_block_delta",
+                    "index": 0,
+                    "delta": {
+                        "type": "signature_delta",
+                        "signature": "sig_123"
+                    }
+                })),
+            )
+            .expect("signature delta should parse");
+
+        assert!(frames.iter().any(|frame| matches!(
+            frame.event,
+            CanonicalStreamEvent::ReasoningSignature(ref signature) if signature == "sig_123"
+        )));
+    }
+
     #[test]
     fn claude_client_emitter_preserves_tool_identity_and_emits_thinking_blocks() {
         let mut emitter = ClaudeClientEmitter::default();
@@ -698,6 +964,15 @@ mod tests {
                 })
                 .expect("reasoning should encode"),
         );
+        bytes.extend(
+            emitter
+                .emit(CanonicalStreamFrame {
+                    id: "msg_123".to_string(),
+                    model: "claude-sonnet-4-5".to_string(),
+                    event: CanonicalStreamEvent::ReasoningSignature("sig_123".to_string()),
+                })
+                .expect("signature should encode"),
+        );
         bytes.extend(
             emitter
                 .emit(CanonicalStreamFrame {
@@ -727,6 +1002,8 @@ mod tests {
         let sse = String::from_utf8(bytes).expect("sse should be utf8");
         assert!(sse.contains("\"type\":\"thinking\""));
         assert!(sse.contains("\"type\":\"thinking_delta\""));
+        assert!(sse.contains("\"type\":\"signature_delta\""));
+        assert!(sse.contains("\"signature\":\"sig_123\""));
         assert!(sse.contains("\"id\":\"toolu_1\""));
         assert!(sse.contains("\"name\":\"lookup\""));
         assert!(sse.contains("\"partial_json\":\"{\\\"city\\\":\\\"Shanghai\\\"}\""));
@@ -753,4 +1030,24 @@ mod tests {
         assert!(sse.contains("\"stop_reason\":\"end_turn\""));
         assert!(sse.contains("\"usage\":{\"input_tokens\":0,\"output_tokens\":0}"));
     }
+
+    #[test]
+    fn claude_client_emitter_emits_image_blocks_for_media_parts() {
+        let mut emitter = ClaudeClientEmitter::default();
+        let bytes = emitter
+            .emit(CanonicalStreamFrame {
+                id: "msg_img_123".to_string(),
+                model: "claude-sonnet-4-5".to_string(),
+                event: CanonicalStreamEvent::ContentPart(CanonicalContentPart::ImageUrl(
+                    "data:image/png;base64,iVBORw0KGgo=".to_string(),
+                )),
+            })
+            .expect("image should encode");
+
+        let sse = String::from_utf8(bytes).expect("sse should be utf8");
+        assert!(sse.contains("\"type\":\"image\""));
+        assert!(sse.contains("\"media_type\":\"image/png\""));
+        assert!(sse.contains("\"data\":\"iVBORw0KGgo=\""));
+        assert!(sse.contains("event: content_block_stop"));
+    }
 }

crates/aether-ai-pipeline/src/finalize/standard/gemini/stream.rs

@@ -23,6 +23,8 @@ pub struct GeminiProviderState {
     finished: bool,
     text_parts: BTreeMap<usize, String>,
     reasoning_parts: BTreeMap<usize, String>,
+    reasoning_signatures: BTreeMap<usize, String>,
+    content_parts: BTreeMap<usize, CanonicalContentPart>,
     tool_calls: BTreeMap<usize, GeminiProviderToolState>,
 }
 
@@ -98,6 +100,13 @@ impl GeminiProviderState {
                 let Some(part_object) = part.as_object() else {
                     continue;
                 };
+                let reasoning_signature = part_object
+                    .get("thoughtSignature")
+                    .or_else(|| part_object.get("thought_signature"))
+                    .and_then(Value::as_str)
+                    .map(str::trim)
+                    .filter(|value| !value.is_empty())
+                    .map(ToOwned::to_owned);
                 if let Some(text) = render_gemini_part_as_text(part_object) {
                     let is_reasoning = part_object
                         .get("thought")
@@ -127,11 +136,43 @@ impl GeminiProviderState {
                             },
                         });
                     }
+                    if is_reasoning {
+                        if let Some(signature) = reasoning_signature.as_ref() {
+                            let previous_signature =
+                                self.reasoning_signatures.entry(index).or_default();
+                            if previous_signature.as_str() != signature.as_str() {
+                                *previous_signature = signature.clone();
+                                out.push(CanonicalStreamFrame {
+                                    id: id.clone(),
+                                    model: model.clone(),
+                                    event: CanonicalStreamEvent::ReasoningSignature(
+                                        signature.clone(),
+                                    ),
+                                });
+                            }
+                        }
+                    }
                     continue;
                 }
                 let Some(function_call) =
                     part_object.get("functionCall").and_then(Value::as_object)
                 else {
+                    if let Some(content_part) = canonical_content_part_from_gemini_part(part_object)
+                    {
+                        let should_emit = self
+                            .content_parts
+                            .get(&index)
+                            .map(|existing| existing != &content_part)
+                            .unwrap_or(true);
+                        if should_emit {
+                            self.content_parts.insert(index, content_part.clone());
+                            out.push(CanonicalStreamFrame {
+                                id: id.clone(),
+                                model: model.clone(),
+                                event: CanonicalStreamEvent::ContentPart(content_part),
+                            });
+                        }
+                    }
                     continue;
                 };
                 let tool_state = self.tool_calls.entry(index).or_default();
@@ -349,6 +390,20 @@ impl GeminiClientEmitter {
             CanonicalStreamEvent::ReasoningDelta(text) => {
                 self.emit_candidate(vec![json!({ "text": text, "thought": true })], None, None)
             }
+            CanonicalStreamEvent::ReasoningSignature(signature) => self.emit_candidate(
+                vec![json!({
+                    "text": "",
+                    "thought": true,
+                    "thoughtSignature": signature,
+                })],
+                None,
+                None,
+            ),
+            CanonicalStreamEvent::ContentPart(part) => self.emit_candidate(
+                vec![gemini_part_from_canonical_content_part(part)],
+                None,
+                None,
+            ),
             CanonicalStreamEvent::ToolCallStart {
                 index,
                 call_id,
@@ -439,6 +494,197 @@ fn render_gemini_part_as_text(part: &Map<String, Value>) -> Option<String> {
     None
 }
 
+fn canonical_content_part_from_gemini_part(
+    part: &Map<String, Value>,
+) -> Option<CanonicalContentPart> {
+    if let Some(image_url) = extract_gemini_image_url(part) {
+        return Some(CanonicalContentPart::ImageUrl(image_url));
+    }
+    if let Some(inline_data) = part
+        .get("inlineData")
+        .or_else(|| part.get("inline_data"))
+        .and_then(Value::as_object)
+    {
+        let mime_type = inline_data
+            .get("mimeType")
+            .or_else(|| inline_data.get("mime_type"))
+            .and_then(Value::as_str)
+            .map(str::trim)
+            .filter(|value| !value.is_empty())?;
+        let data = inline_data
+            .get("data")
+            .and_then(Value::as_str)
+            .map(str::trim)
+            .filter(|value| !value.is_empty())?;
+        if let Some(format) = mime_type.strip_prefix("audio/") {
+            return Some(CanonicalContentPart::Audio {
+                data: data.to_string(),
+                format: format.to_string(),
+            });
+        }
+        return Some(CanonicalContentPart::File {
+            file_data: Some(format!("data:{mime_type};base64,{data}")),
+            reference: None,
+            mime_type: Some(mime_type.to_string()),
+            filename: None,
+        });
+    }
+    let file_data = part
+        .get("fileData")
+        .or_else(|| part.get("file_data"))
+        .and_then(Value::as_object)?;
+    let reference = file_data
+        .get("fileUri")
+        .or_else(|| file_data.get("file_uri"))
+        .and_then(Value::as_str)
+        .map(str::trim)
+        .filter(|value| !value.is_empty())?;
+    Some(CanonicalContentPart::File {
+        file_data: None,
+        reference: Some(reference.to_string()),
+        mime_type: file_data
+            .get("mimeType")
+            .or_else(|| file_data.get("mime_type"))
+            .and_then(Value::as_str)
+            .map(ToOwned::to_owned),
+        filename: None,
+    })
+}
+
+fn gemini_part_from_canonical_content_part(part: CanonicalContentPart) -> Value {
+    match part {
+        CanonicalContentPart::ImageUrl(url) => {
+            if let Some((mime_type, data)) = parse_data_url(url.as_str()) {
+                json!({
+                    "inlineData": {
+                        "mimeType": mime_type,
+                        "data": data,
+                    }
+                })
+            } else {
+                json!({
+                    "fileData": {
+                        "fileUri": url.clone(),
+                        "mimeType": guess_media_type_from_reference(url.as_str(), "image/jpeg"),
+                    }
+                })
+            }
+        }
+        CanonicalContentPart::File {
+            file_data,
+            reference,
+            mime_type,
+            ..
+        } => {
+            if let Some(file_data) = file_data {
+                if let Some((mime_type, data)) = parse_data_url(file_data.as_str()) {
+                    json!({
+                        "inlineData": {
+                            "mimeType": mime_type,
+                            "data": data,
+                        }
+                    })
+                } else {
+                    json!({ "text": "[File]" })
+                }
+            } else if let Some(reference) = reference {
+                json!({
+                    "fileData": {
+                        "fileUri": reference.clone(),
+                        "mimeType": mime_type.unwrap_or_else(|| {
+                            guess_media_type_from_reference(reference.as_str(), "application/octet-stream")
+                        }),
+                    }
+                })
+            } else {
+                json!({ "text": "[File]" })
+            }
+        }
+        CanonicalContentPart::Audio { data, format } => json!({
+            "inlineData": {
+                "mimeType": format!("audio/{format}"),
+                "data": data,
+            }
+        }),
+    }
+}
+
+fn extract_gemini_image_url(part: &Map<String, Value>) -> Option<String> {
+    let inline_data = part
+        .get("inlineData")
+        .or_else(|| part.get("inline_data"))
+        .and_then(Value::as_object)?;
+    if !inline_data
+        .get("mimeType")
+        .or_else(|| inline_data.get("mime_type"))
+        .and_then(Value::as_str)
+        .is_some_and(|value| value.starts_with("image/"))
+    {
+        return None;
+    }
+    if let Some(data) = inline_data
+        .get("data")
+        .and_then(Value::as_str)
+        .map(str::trim)
+        .filter(|value| !value.is_empty())
+    {
+        let mime_type = inline_data
+            .get("mimeType")
+            .or_else(|| inline_data.get("mime_type"))
+            .and_then(Value::as_str)
+            .unwrap_or("image/jpeg");
+        return Some(format!("data:{mime_type};base64,{data}"));
+    }
+    let file_data = part
+        .get("fileData")
+        .or_else(|| part.get("file_data"))
+        .and_then(Value::as_object)?;
+    if !file_data
+        .get("mimeType")
+        .or_else(|| file_data.get("mime_type"))
+        .and_then(Value::as_str)
+        .is_some_and(|value| value.starts_with("image/"))
+    {
+        return None;
+    }
+    file_data
+        .get("fileUri")
+        .or_else(|| file_data.get("file_uri"))
+        .and_then(Value::as_str)
+        .map(ToOwned::to_owned)
+}
+
+fn parse_data_url(value: &str) -> Option<(String, String)> {
+    let rest = value.strip_prefix("data:")?;
+    let (meta, data) = rest.split_once(',')?;
+    let mime_type = meta.strip_suffix(";base64")?;
+    if mime_type.trim().is_empty() || data.trim().is_empty() {
+        return None;
+    }
+    Some((mime_type.to_string(), data.to_string()))
+}
+
+fn guess_media_type_from_reference(reference: &str, default_mime: &str) -> String {
+    let normalized = reference
+        .split('?')
+        .next()
+        .unwrap_or(reference)
+        .to_ascii_lowercase();
+    if normalized.ends_with(".png") {
+        "image/png".to_string()
+    } else if normalized.ends_with(".gif") {
+        "image/gif".to_string()
+    } else if normalized.ends_with(".webp") {
+        "image/webp".to_string()
+    } else if normalized.ends_with(".jpg") || normalized.ends_with(".jpeg") {
+        "image/jpeg".to_string()
+    } else if normalized.ends_with(".pdf") {
+        "application/pdf".to_string()
+    } else {
+        default_mime.to_string()
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;
@@ -463,7 +709,7 @@ mod tests {
                         "finishReason": "RECITATION",
                         "content": {
                             "parts": [
-                                { "text": "reason", "thought": true },
+                                { "text": "reason", "thought": true, "thoughtSignature": "sig_123" },
                                 { "executableCode": { "language": "python", "code": "print(1)" } }
                             ]
                         }
@@ -482,6 +728,10 @@ mod tests {
             frame.event,
             CanonicalStreamEvent::ReasoningDelta(ref text) if text == "reason"
         )));
+        assert!(frames.iter().any(|frame| matches!(
+            frame.event,
+            CanonicalStreamEvent::ReasoningSignature(ref signature) if signature == "sig_123"
+        )));
         assert!(frames.iter().any(|frame| matches!(
             frame.event,
             CanonicalStreamEvent::TextDelta(ref text) if text == "```python\nprint(1)\n```"
@@ -503,6 +753,15 @@ mod tests {
                 event: CanonicalStreamEvent::ReasoningDelta("reason".to_string()),
             })
             .expect("reasoning should encode");
+        bytes.extend(
+            emitter
+                .emit(CanonicalStreamFrame {
+                    id: "resp_123".to_string(),
+                    model: "gemini-2.5-pro".to_string(),
+                    event: CanonicalStreamEvent::ReasoningSignature("sig_123".to_string()),
+                })
+                .expect("signature should encode"),
+        );
         bytes.extend(
             emitter
                 .emit(CanonicalStreamFrame {
@@ -523,6 +782,55 @@ mod tests {
 
         let sse = String::from_utf8(bytes).expect("sse should be utf8");
         assert!(sse.contains("\"thought\":true"));
+        assert!(sse.contains("\"thoughtSignature\":\"sig_123\""));
         assert!(sse.contains("\"finishReason\":\"STOP\""));
     }
+
+    #[test]
+    fn gemini_provider_state_parses_inline_image_parts() {
+        let mut state = GeminiProviderState::default();
+        let report_context = json!({});
+        let frames = state
+            .push_line(
+                &report_context,
+                data_line(json!({
+                    "responseId": "resp_media_123",
+                    "modelVersion": "gemini-2.5-pro",
+                    "candidates": [{
+                        "index": 0,
+                        "content": {
+                            "parts": [
+                                { "inlineData": { "mimeType": "image/png", "data": "iVBORw0KGgo=" } }
+                            ]
+                        }
+                    }]
+                })),
+            )
+            .expect("chunk should parse");
+
+        assert!(frames.iter().any(|frame| matches!(
+            frame.event,
+            CanonicalStreamEvent::ContentPart(CanonicalContentPart::ImageUrl(ref url))
+                if url == "data:image/png;base64,iVBORw0KGgo="
+        )));
+    }
+
+    #[test]
+    fn gemini_client_emitter_emits_inline_image_parts() {
+        let mut emitter = GeminiClientEmitter::default();
+        let bytes = emitter
+            .emit(CanonicalStreamFrame {
+                id: "resp_img_123".to_string(),
+                model: "gemini-2.5-pro".to_string(),
+                event: CanonicalStreamEvent::ContentPart(CanonicalContentPart::ImageUrl(
+                    "data:image/png;base64,iVBORw0KGgo=".to_string(),
+                )),
+            })
+            .expect("image should encode");
+
+        let sse = String::from_utf8(bytes).expect("sse should be utf8");
+        assert!(
+            sse.contains("\"inlineData\":{\"mimeType\":\"image/png\",\"data\":\"iVBORw0KGgo=\"}")
+        );
+    }
 }

crates/aether-ai-pipeline/src/finalize/standard/openai/stream.rs

@@ -1024,6 +1024,24 @@ impl OpenAIChatClientEmitter {
                 )?);
                 Ok(out)
             }
+            CanonicalStreamEvent::ReasoningSignature(_) => Ok(Vec::new()),
+            CanonicalStreamEvent::ContentPart(part) => {
+                let placeholder = openai_stream_placeholder_for_content_part(&part);
+                let mut out = self.ensure_started()?;
+                out.extend(encode_json_sse(
+                    None,
+                    &build_openai_chat_chunk(
+                        self.response_id
+                            .as_deref()
+                            .unwrap_or("chatcmpl-local-stream"),
+                        self.model.as_deref().unwrap_or("unknown"),
+                        placeholder,
+                        None,
+                        None,
+                    ),
+                )?);
+                Ok(out)
+            }
             CanonicalStreamEvent::ToolCallStart {
                 index,
                 call_id,
@@ -1602,6 +1620,24 @@ impl OpenAICliClientEmitter {
                 )?);
                 Ok(out)
             }
+            CanonicalStreamEvent::ReasoningSignature(_) => Ok(Vec::new()),
+            CanonicalStreamEvent::ContentPart(part) => {
+                let placeholder = openai_stream_placeholder_for_content_part(&part);
+                let mut out = self.ensure_text_item_started()?;
+                self.text.push_str(&placeholder);
+                out.extend(self.encode_response_event(
+                    "response.output_text.delta",
+                    json!({
+                        "type": "response.output_text.delta",
+                        "response_id": self.response_id(),
+                        "output_index": self.message_output_index.unwrap_or(0),
+                        "item_id": self.message_item_id(),
+                        "content_index": 0,
+                        "delta": placeholder,
+                    }),
+                )?);
+                Ok(out)
+            }
             CanonicalStreamEvent::ToolCallStart {
                 index,
                 call_id,
@@ -1715,6 +1751,30 @@ impl OpenAICliClientEmitter {
     }
 }
 
+fn openai_stream_placeholder_for_content_part(part: &CanonicalContentPart) -> String {
+    match part {
+        CanonicalContentPart::ImageUrl(url) => {
+            if url.starts_with("data:") {
+                "[Image]".to_string()
+            } else {
+                format!("[Image: {url}]")
+            }
+        }
+        CanonicalContentPart::File {
+            reference,
+            mime_type,
+            filename,
+            ..
+        } => reference
+            .as_ref()
+            .map(|value| format!("[File: {value}]"))
+            .or_else(|| filename.as_ref().map(|value| format!("[File: {value}]")))
+            .or_else(|| mime_type.as_ref().map(|value| format!("[File: {value}]")))
+            .unwrap_or_else(|| "[File]".to_string()),
+        CanonicalContentPart::Audio { format, .. } => format!("[Audio: {format}]"),
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;
@@ -1975,6 +2035,23 @@ mod tests {
         assert!(sse.contains("\"reasoning_content\":\"because\""));
     }
 
+    #[test]
+    fn openai_chat_client_emitter_renders_image_parts_as_placeholder() {
+        let mut emitter = OpenAIChatClientEmitter::default();
+        let bytes = emitter
+            .emit(CanonicalStreamFrame {
+                id: "chatcmpl_img_123".to_string(),
+                model: "gpt-5.4".to_string(),
+                event: CanonicalStreamEvent::ContentPart(CanonicalContentPart::ImageUrl(
+                    "data:image/png;base64,iVBORw0KGgo=".to_string(),
+                )),
+            })
+            .expect("image should encode");
+
+        let sse = String::from_utf8(bytes).expect("sse should be utf8");
+        assert!(sse.contains("[Image]"));
+    }
+
     #[test]
     fn openai_chat_client_emitter_emits_usage_only_final_chunk() {
         let mut emitter = OpenAIChatClientEmitter::default();

crates/aether-ai-pipeline/src/finalize/standard/stream_core/common.rs

@@ -11,11 +11,28 @@ pub struct CanonicalUsage {
     pub cache_read_tokens: u64,
 }
 
+#[derive(Clone, Debug, PartialEq, Eq)]
+pub enum CanonicalContentPart {
+    ImageUrl(String),
+    File {
+        file_data: Option<String>,
+        reference: Option<String>,
+        mime_type: Option<String>,
+        filename: Option<String>,
+    },
+    Audio {
+        data: String,
+        format: String,
+    },
+}
+
 #[derive(Clone, Debug)]
 pub enum CanonicalStreamEvent {
     Start,
     TextDelta(String),
     ReasoningDelta(String),
+    ReasoningSignature(String),
+    ContentPart(CanonicalContentPart),
     ToolCallStart {
         index: usize,
         call_id: String,

crates/aether-ai-pipeline/src/finalize/standard/stream_core/format_matrix.rs

@@ -696,6 +696,63 @@ mod tests {
         }
     }
 
+    #[test]
+    fn rewrites_gemini_inline_image_streams_to_claude_image_blocks() {
+        let report_context = report_context("gemini:chat", "claude:chat");
+        let mut matrix = StreamingStandardFormatMatrix::default();
+        let output = matrix
+            .transform_line(
+                &report_context,
+                data_line(json!({
+                    "responseId": "resp_media_123",
+                    "modelVersion": "gemini-2.5-pro",
+                    "candidates": [{
+                        "index": 0,
+                        "content": {
+                            "parts": [
+                                { "inlineData": { "mimeType": "image/png", "data": "iVBORw0KGgo=" } }
+                            ]
+                        }
+                    }]
+                })),
+            )
+            .expect("image chunk should rewrite");
+        let sse = String::from_utf8(output).expect("sse should be utf8");
+
+        assert!(sse.contains("event: message_start"));
+        assert!(sse.contains("\"type\":\"image\""));
+        assert!(sse.contains("\"media_type\":\"image/png\""));
+        assert!(sse.contains("\"data\":\"iVBORw0KGgo=\""));
+    }
+
+    #[test]
+    fn rewrites_claude_image_blocks_to_gemini_inline_image_streams() {
+        let report_context = report_context("claude:chat", "gemini:chat");
+        let mut matrix = StreamingStandardFormatMatrix::default();
+        let output = matrix
+            .transform_line(
+                &report_context,
+                data_line(json!({
+                    "type": "content_block_start",
+                    "index": 0,
+                    "content_block": {
+                        "type": "image",
+                        "source": {
+                            "type": "base64",
+                            "media_type": "image/png",
+                            "data": "iVBORw0KGgo="
+                        }
+                    }
+                })),
+            )
+            .expect("image chunk should rewrite");
+        let sse = String::from_utf8(output).expect("sse should be utf8");
+
+        assert!(
+            sse.contains("\"inlineData\":{\"mimeType\":\"image/png\",\"data\":\"iVBORw0KGgo=\"}")
+        );
+    }
+
     #[test]
     fn terminal_observer_preserves_claude_cache_usage() {
         let report_context = report_context("claude:chat", "openai:chat");

crates/aether-ai-pipeline/src/finalize/sync_products.rs

@@ -11,6 +11,11 @@ use crate::conversion::response::{
     convert_openai_chat_response_to_openai_cli, convert_openai_cli_response_to_openai_chat,
 };
 use crate::conversion::{sync_chat_response_conversion_kind, sync_cli_response_conversion_kind};
+use crate::finalize::standard::gemini::stream::GeminiProviderState;
+use crate::finalize::standard::stream_core::common::{
+    map_openai_finish_reason_to_gemini, parse_json_arguments_value, CanonicalContentPart,
+    CanonicalStreamEvent, CanonicalUsage,
+};
 
 #[derive(Clone, Debug, PartialEq)]
 pub struct StandardCrossFormatSyncProduct {
@@ -682,6 +687,7 @@ struct OpenAIChatToolCallState {
 struct ClaudeContentBlockState {
     object: Map<String, Value>,
     text: String,
+    signature: Option<String>,
     partial_json: String,
 }
 
@@ -1528,6 +1534,14 @@ fn materialize_openai_cli_tool_item(output_index: usize, state: OpenAICliSyncToo
     Value::Object(item)
 }
 
+#[derive(Default)]
+struct GeminiSyncToolState {
+    call_id: String,
+    name: String,
+    arguments: String,
+    part_index: Option<usize>,
+}
+
 pub fn aggregate_claude_stream_sync_response(body: &[u8]) -> Option<Value> {
     let events = parse_stream_json_events(body)?;
     if events.is_empty() {
@@ -1599,6 +1613,22 @@ pub fn aggregate_claude_stream_sync_response(body: &[u8]) -> Option<Value> {
                             state.partial_json.push_str(partial_json);
                         }
                     }
+                    "thinking_delta" => {
+                        if let Some(thinking) = delta
+                            .get("thinking")
+                            .and_then(Value::as_str)
+                            .or_else(|| delta.get("text").and_then(Value::as_str))
+                        {
+                            state.text.push_str(thinking);
+                        }
+                    }
+                    "signature_delta" => {
+                        if let Some(signature) = delta.get("signature").and_then(Value::as_str) {
+                            if !signature.is_empty() {
+                                state.signature = Some(signature.to_string());
+                            }
+                        }
+                    }
                     _ => {}
                 }
             }
@@ -1650,6 +1680,23 @@ pub fn aggregate_claude_stream_sync_response(body: &[u8]) -> Option<Value> {
                     }),
                 );
             }
+            "thinking" => {
+                block.insert(
+                    "thinking".to_string(),
+                    Value::String(if state.text.is_empty() {
+                        block
+                            .get("thinking")
+                            .and_then(Value::as_str)
+                            .unwrap_or_default()
+                            .to_string()
+                    } else {
+                        state.text
+                    }),
+                );
+                if let Some(signature) = state.signature {
+                    block.insert("signature".to_string(), Value::String(signature));
+                }
+            }
             "tool_use" => {
                 if !state.partial_json.is_empty() {
                     let input = serde_json::from_str::<Value>(&state.partial_json)
@@ -1661,6 +1708,9 @@ pub fn aggregate_claude_stream_sync_response(body: &[u8]) -> Option<Value> {
                 if !state.text.is_empty() {
                     block.insert("text".to_string(), Value::String(state.text));
                 }
+                if let Some(signature) = state.signature {
+                    block.insert("signature".to_string(), Value::String(signature));
+                }
             }
         }
         content.push(Value::Object(block));
@@ -1679,15 +1729,22 @@ pub fn aggregate_gemini_stream_sync_response(body: &[u8]) -> Option<Value> {
         return None;
     }
 
-    let mut candidates: BTreeMap<usize, Value> = BTreeMap::new();
+    let report_context = Value::Object(Map::new());
+    let mut provider = GeminiProviderState::default();
     let mut response_id: Option<Value> = None;
     let mut private_response_id: Option<Value> = None;
     let mut model_version: Option<Value> = None;
     let mut usage_metadata: Option<Value> = None;
     let mut prompt_feedback: Option<Value> = None;
+    let mut candidate: Map<String, Value> = Map::new();
+    let mut role: Option<Value> = None;
     let mut saw_candidate = false;
+    let mut parts: Vec<Value> = Vec::new();
+    let mut tool_states: BTreeMap<usize, GeminiSyncToolState> = BTreeMap::new();
+    let mut finish_reason: Option<String> = None;
+    let mut usage_from_frames: Option<CanonicalUsage> = None;
 
-    for event in events {
+    for event in &events {
         let raw_event_object = event.as_object()?;
         if let Some(id) = raw_event_object.get("responseId") {
             response_id = Some(id.clone());
@@ -1723,24 +1780,142 @@ pub fn aggregate_gemini_stream_sync_response(body: &[u8]) -> Option<Value> {
         else {
             continue;
         };
-        for candidate in event_candidates {
+        for event_candidate in event_candidates {
-            let Some(candidate_object) = candidate.as_object() else {
+            let Some(candidate_object) = event_candidate.as_object() else {
                 continue;
             };
-            let index = candidate_object
+            for (key, value) in candidate_object {
-                .get("index")
+                if key != "content" {
-                .and_then(Value::as_u64)
+                    candidate.insert(key.clone(), value.clone());
-                .map(|value| value as usize)
+                }
-                .unwrap_or(0);
+            }
-            candidates.insert(index, Value::Object(candidate_object.clone()));
+            if let Some(content) = candidate_object.get("content").and_then(Value::as_object) {
+                if let Some(content_role) = content.get("role") {
+                    role = Some(content_role.clone());
+                }
+            }
             saw_candidate = true;
         }
+
+        let line = format!("data: {event}\n").into_bytes();
+        let frames = provider.push_line(&report_context, line).ok()?;
+        for frame in frames {
+            if response_id.is_none() && !frame.id.is_empty() {
+                response_id = Some(Value::String(frame.id.clone()));
+            }
+            if model_version.is_none() && !frame.model.is_empty() {
+                model_version = Some(Value::String(frame.model.clone()));
+            }
+            match frame.event {
+                CanonicalStreamEvent::Start => {}
+                CanonicalStreamEvent::TextDelta(text) => {
+                    append_gemini_text_part(&mut parts, text, false);
+                }
+                CanonicalStreamEvent::ReasoningDelta(text) => {
+                    append_gemini_text_part(&mut parts, text, true);
+                }
+                CanonicalStreamEvent::ReasoningSignature(signature) => {
+                    attach_gemini_reasoning_signature(&mut parts, signature);
+                }
+                CanonicalStreamEvent::ContentPart(part) => {
+                    parts.push(gemini_sync_part_from_canonical_content_part(part));
+                }
+                CanonicalStreamEvent::ToolCallStart {
+                    index,
+                    call_id,
+                    name,
+                } => {
+                    let generated_call_id = if call_id.trim().is_empty() {
+                        format!("call_auto_{index}")
+                    } else {
+                        call_id
+                    };
+                    let generated_name = if name.trim().is_empty() {
+                        "unknown".to_string()
+                    } else {
+                        name
+                    };
+                    let state = tool_states.entry(index).or_default();
+                    state.call_id = generated_call_id;
+                    state.name = generated_name;
+                    if state.part_index.is_none() {
+                        let part_index = parts.len();
+                        parts.push(sync_gemini_function_call_part(state));
+                        state.part_index = Some(part_index);
+                    } else if let Some(part_index) = state.part_index {
+                        parts[part_index] = sync_gemini_function_call_part(state);
+                    }
+                }
+                CanonicalStreamEvent::ToolCallArgumentsDelta { index, arguments } => {
+                    let state = tool_states.entry(index).or_default();
+                    state.arguments.push_str(&arguments);
+                    let part_index = if let Some(part_index) = state.part_index {
+                        part_index
+                    } else {
+                        let part_index = parts.len();
+                        parts.push(sync_gemini_function_call_part(state));
+                        state.part_index = Some(part_index);
+                        part_index
+                    };
+                    parts[part_index] = sync_gemini_function_call_part(state);
+                }
+                CanonicalStreamEvent::Finish {
+                    finish_reason: frame_finish_reason,
+                    usage,
+                } => {
+                    finish_reason = frame_finish_reason
+                        .map(|value| {
+                            map_openai_finish_reason_to_gemini(Some(value.as_str())).to_string()
+                        })
+                        .or(finish_reason);
+                    if usage.is_some() {
+                        usage_from_frames = usage;
+                    }
+                }
+            }
+        }
+    }
+
+    let frames = provider.finish(&report_context).ok()?;
+    for frame in frames {
+        if response_id.is_none() && !frame.id.is_empty() {
+            response_id = Some(Value::String(frame.id.clone()));
+        }
+        if model_version.is_none() && !frame.model.is_empty() {
+            model_version = Some(Value::String(frame.model.clone()));
+        }
+        if let CanonicalStreamEvent::Finish {
+            finish_reason: frame_finish_reason,
+            usage,
+        } = frame.event
+        {
+            finish_reason = frame_finish_reason
+                .map(|value| map_openai_finish_reason_to_gemini(Some(value.as_str())).to_string())
+                .or(finish_reason);
+            if usage.is_some() {
+                usage_from_frames = usage;
+            }
+        }
     }
 
     if !saw_candidate {
         return None;
     }
 
+    candidate.insert(
+        "content".to_string(),
+        json!({
+            "role": role.unwrap_or_else(|| Value::String("model".to_string())),
+            "parts": parts,
+        }),
+    );
+    candidate
+        .entry("index".to_string())
+        .or_insert_with(|| Value::from(0_u64));
+    if let Some(finish_reason) = finish_reason {
+        candidate.insert("finishReason".to_string(), Value::String(finish_reason));
+    }
+
     let mut response = Map::new();
     if let Some(response_id) = response_id {
         response.insert("responseId".to_string(), response_id);
@@ -1750,11 +1925,14 @@ pub fn aggregate_gemini_stream_sync_response(body: &[u8]) -> Option<Value> {
     }
     response.insert(
         "candidates".to_string(),
-        Value::Array(candidates.into_values().collect()),
+        Value::Array(vec![Value::Object(candidate)]),
     );
     if let Some(version) = model_version {
         response.insert("modelVersion".to_string(), version);
     }
+    if usage_metadata.is_none() {
+        usage_metadata = usage_from_frames.map(gemini_usage_metadata_from_canonical);
+    }
     if let Some(usage) = usage_metadata {
         response.insert("usageMetadata".to_string(), usage);
     }
@@ -1764,9 +1942,204 @@ pub fn aggregate_gemini_stream_sync_response(body: &[u8]) -> Option<Value> {
     Some(Value::Object(response))
 }
 
+fn append_gemini_text_part(parts: &mut Vec<Value>, text: String, thought: bool) {
+    if text.is_empty() {
+        return;
+    }
+    let Some(existing) = parts
+        .last_mut()
+        .and_then(Value::as_object_mut)
+        .filter(|part| is_mergeable_gemini_text_part(part, thought))
+    else {
+        let mut part = Map::new();
+        part.insert("text".to_string(), Value::String(text));
+        if thought {
+            part.insert("thought".to_string(), Value::Bool(true));
+        }
+        parts.push(Value::Object(part));
+        return;
+    };
+    let current = existing
+        .get("text")
+        .and_then(Value::as_str)
+        .unwrap_or_default();
+    existing.insert(
+        "text".to_string(),
+        Value::String(format!("{current}{text}")),
+    );
+}
+
+fn attach_gemini_reasoning_signature(parts: &mut Vec<Value>, signature: String) {
+    if signature.is_empty() {
+        return;
+    }
+    for part in parts.iter_mut().rev() {
+        let Some(part_object) = part.as_object_mut() else {
+            continue;
+        };
+        if is_mergeable_gemini_text_part(part_object, true) {
+            part_object.insert(
+                "thoughtSignature".to_string(),
+                Value::String(signature.clone()),
+            );
+            return;
+        }
+    }
+    parts.push(json!({
+        "text": "",
+        "thought": true,
+        "thoughtSignature": signature,
+    }));
+}
+
+fn is_mergeable_gemini_text_part(part: &Map<String, Value>, thought: bool) -> bool {
+    if !part.contains_key("text") {
+        return false;
+    }
+    if part
+        .get("thought")
+        .and_then(Value::as_bool)
+        .unwrap_or(false)
+        != thought
+    {
+        return false;
+    }
+    part.keys().all(|key| {
+        matches!(
+            key.as_str(),
+            "text" | "thought" | "thoughtSignature" | "thought_signature"
+        )
+    })
+}
+
+fn sync_gemini_function_call_part(state: &GeminiSyncToolState) -> Value {
+    json!({
+        "functionCall": {
+            "id": if state.call_id.trim().is_empty() {
+                "call_auto_0".to_string()
+            } else {
+                state.call_id.clone()
+            },
+            "name": if state.name.trim().is_empty() {
+                "unknown".to_string()
+            } else {
+                state.name.clone()
+            },
+            "args": sync_gemini_function_args_value(&state.arguments),
+        }
+    })
+}
+
+fn sync_gemini_function_args_value(arguments: &str) -> Value {
+    match parse_json_arguments_value(arguments) {
+        Some(Value::Object(map)) => Value::Object(map),
+        Some(value) => json!({ "raw": value }),
+        None if arguments.trim().is_empty() => Value::Object(Map::new()),
+        None => json!({ "raw": arguments }),
+    }
+}
+
+fn gemini_sync_part_from_canonical_content_part(part: CanonicalContentPart) -> Value {
+    match part {
+        CanonicalContentPart::ImageUrl(url) => {
+            if let Some((mime_type, data)) = parse_data_url(url.as_str()) {
+                json!({
+                    "inlineData": {
+                        "mimeType": mime_type,
+                        "data": data,
+                    }
+                })
+            } else {
+                json!({
+                    "fileData": {
+                        "fileUri": url.clone(),
+                        "mimeType": guess_media_type_from_reference(url.as_str(), "image/jpeg"),
+                    }
+                })
+            }
+        }
+        CanonicalContentPart::File {
+            file_data,
+            reference,
+            mime_type,
+            ..
+        } => {
+            if let Some(file_data) = file_data {
+                if let Some((mime_type, data)) = parse_data_url(file_data.as_str()) {
+                    json!({
+                        "inlineData": {
+                            "mimeType": mime_type,
+                            "data": data,
+                        }
+                    })
+                } else {
+                    json!({ "text": "[File]" })
+                }
+            } else if let Some(reference) = reference {
+                json!({
+                    "fileData": {
+                        "fileUri": reference.clone(),
+                        "mimeType": mime_type.unwrap_or_else(|| {
+                            guess_media_type_from_reference(reference.as_str(), "application/octet-stream")
+                        }),
+                    }
+                })
+            } else {
+                json!({ "text": "[File]" })
+            }
+        }
+        CanonicalContentPart::Audio { data, format } => json!({
+            "inlineData": {
+                "mimeType": format!("audio/{format}"),
+                "data": data,
+            }
+        }),
+    }
+}
+
+fn gemini_usage_metadata_from_canonical(usage: CanonicalUsage) -> Value {
+    json!({
+        "promptTokenCount": usage.input_tokens,
+        "candidatesTokenCount": usage.output_tokens,
+        "totalTokenCount": usage.total_tokens,
+    })
+}
+
+fn parse_data_url(value: &str) -> Option<(String, String)> {
+    let rest = value.strip_prefix("data:")?;
+    let (meta, data) = rest.split_once(',')?;
+    let mime_type = meta.strip_suffix(";base64")?;
+    if mime_type.trim().is_empty() || data.trim().is_empty() {
+        return None;
+    }
+    Some((mime_type.to_string(), data.to_string()))
+}
+
+fn guess_media_type_from_reference(reference: &str, default_mime: &str) -> String {
+    let normalized = reference
+        .split('?')
+        .next()
+        .unwrap_or(reference)
+        .to_ascii_lowercase();
+    if normalized.ends_with(".png") {
+        "image/png".to_string()
+    } else if normalized.ends_with(".gif") {
+        "image/gif".to_string()
+    } else if normalized.ends_with(".webp") {
+        "image/webp".to_string()
+    } else if normalized.ends_with(".jpg") || normalized.ends_with(".jpeg") {
+        "image/jpeg".to_string()
+    } else if normalized.ends_with(".pdf") {
+        "application/pdf".to_string()
+    } else {
+        default_mime.to_string()
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::{
+        aggregate_claude_stream_sync_response, aggregate_gemini_stream_sync_response,
         maybe_build_openai_chat_cross_format_sync_product_from_normalized_payload,
         maybe_build_openai_cli_cross_format_sync_product_from_normalized_payload,
         maybe_build_openai_cli_same_family_sync_body_from_normalized_payload,
@@ -1778,6 +2151,104 @@ mod tests {
     use base64::Engine as _;
     use serde_json::json;
 
+    #[test]
+    fn aggregates_claude_stream_thinking_signatures_into_sync_body() {
+        let body = concat!(
+            "event: message_start\n",
+            "data: {\"type\":\"message_start\",\"message\":{\"id\":\"msg_123\",\"type\":\"message\",\"role\":\"assistant\",\"model\":\"claude-sonnet-4-5\",\"content\":[],\"stop_reason\":null,\"stop_sequence\":null,\"usage\":{\"input_tokens\":1,\"output_tokens\":0}}}\n\n",
+            "event: content_block_start\n",
+            "data: {\"type\":\"content_block_start\",\"index\":0,\"content_block\":{\"type\":\"thinking\",\"thinking\":\"\"}}\n\n",
+            "event: content_block_delta\n",
+            "data: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"thinking_delta\",\"thinking\":\"step by step\"}}\n\n",
+            "event: content_block_delta\n",
+            "data: {\"type\":\"content_block_delta\",\"index\":0,\"delta\":{\"type\":\"signature_delta\",\"signature\":\"sig_123\"}}\n\n",
+            "event: message_delta\n",
+            "data: {\"type\":\"message_delta\",\"delta\":{\"stop_reason\":\"end_turn\",\"stop_sequence\":null},\"usage\":{\"input_tokens\":1,\"output_tokens\":2}}\n\n",
+            "event: message_stop\n",
+            "data: {\"type\":\"message_stop\"}\n\n",
+        );
+
+        let aggregated =
+            aggregate_claude_stream_sync_response(body.as_bytes()).expect("body should aggregate");
+
+        assert_eq!(aggregated["content"][0]["type"], "thinking");
+        assert_eq!(aggregated["content"][0]["thinking"], "step by step");
+        assert_eq!(aggregated["content"][0]["signature"], "sig_123");
+        assert_eq!(aggregated["usage"]["output_tokens"], 2);
+    }
+
+    #[test]
+    fn aggregates_gemini_stream_deltas_media_and_signatures_into_sync_body() {
+        let body = concat!(
+            "data: {\"responseId\":\"resp_gem_stream_123\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[{\"text\":\"rea\",\"thought\":true}]}}]}\n\n",
+            "data: {\"responseId\":\"resp_gem_stream_123\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[{\"text\":\"son\",\"thought\":true}]}}]}\n\n",
+            "data: {\"responseId\":\"resp_gem_stream_123\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[{\"text\":\"\",\"thought\":true,\"thoughtSignature\":\"sig_123\"}]}}]}\n\n",
+            "data: {\"responseId\":\"resp_gem_stream_123\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[{\"inlineData\":{\"mimeType\":\"image/png\",\"data\":\"iVBORw0KGgo=\"}}]}}]}\n\n",
+            "data: {\"responseId\":\"resp_gem_stream_123\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[]},\"finishReason\":\"STOP\"}],\"usageMetadata\":{\"promptTokenCount\":2,\"candidatesTokenCount\":3,\"totalTokenCount\":5}}\n\n",
+        );
+
+        let aggregated =
+            aggregate_gemini_stream_sync_response(body.as_bytes()).expect("body should aggregate");
+
+        assert_eq!(aggregated["responseId"], "resp_gem_stream_123");
+        assert_eq!(
+            aggregated["candidates"][0]["content"]["parts"][0]["text"],
+            "reason"
+        );
+        assert_eq!(
+            aggregated["candidates"][0]["content"]["parts"][0]["thoughtSignature"],
+            "sig_123"
+        );
+        assert_eq!(
+            aggregated["candidates"][0]["content"]["parts"][1]["inlineData"]["mimeType"],
+            "image/png"
+        );
+        assert_eq!(aggregated["candidates"][0]["finishReason"], "STOP");
+        assert_eq!(aggregated["usageMetadata"]["totalTokenCount"], 5);
+    }
+
+    #[test]
+    fn builds_openai_chat_cross_format_sync_product_from_gemini_stream_with_media_and_signature() {
+        let body = concat!(
+            "data: {\"responseId\":\"resp_gem_stream_456\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[{\"text\":\"thinking\",\"thought\":true}]}}]}\n\n",
+            "data: {\"responseId\":\"resp_gem_stream_456\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[{\"text\":\"\",\"thought\":true,\"thoughtSignature\":\"sig_456\"}]}}]}\n\n",
+            "data: {\"responseId\":\"resp_gem_stream_456\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[{\"inlineData\":{\"mimeType\":\"image/png\",\"data\":\"iVBORw0KGgo=\"}}]}}]}\n\n",
+            "data: {\"responseId\":\"resp_gem_stream_456\",\"modelVersion\":\"gemini-2.5-pro\",\"candidates\":[{\"index\":0,\"content\":{\"role\":\"model\",\"parts\":[]},\"finishReason\":\"STOP\"}],\"usageMetadata\":{\"promptTokenCount\":4,\"candidatesTokenCount\":2,\"totalTokenCount\":6}}\n\n",
+        );
+        let report_context = json!({
+            "provider_api_format": "gemini:chat",
+            "client_api_format": "openai:chat",
+            "mapped_model": "gemini-2.5-pro",
+        });
+
+        let product = maybe_build_standard_cross_format_sync_product_from_normalized_payload(
+            "openai_chat_sync_finalize",
+            200,
+            Some(&report_context),
+            None,
+            Some(&base64::engine::general_purpose::STANDARD.encode(body)),
+        )
+        .expect("product build should succeed")
+        .expect("product should exist");
+
+        assert_eq!(
+            product.provider_body_json["candidates"][0]["content"]["parts"][0]["thoughtSignature"],
+            "sig_456"
+        );
+        assert_eq!(
+            product.client_body_json["choices"][0]["message"]["reasoning_parts"][0]["signature"],
+            "sig_456"
+        );
+        assert_eq!(
+            product.client_body_json["choices"][0]["message"]["content"][0]["type"],
+            "image_url"
+        );
+        assert_eq!(
+            product.client_body_json["choices"][0]["message"]["content"][0]["image_url"]["url"],
+            "data:image/png;base64,iVBORw0KGgo="
+        );
+    }
+
     #[test]
     fn builds_standard_cross_format_sync_product_from_normalized_stream_payload() {
         let body = concat!(