diff --git a/litellm-rust/crates/cache/src/semantic.rs b/litellm-rust/crates/cache/src/semantic.rs
index b27ab269edd..990f5e47aa8 100644
--- a/litellm-rust/crates/cache/src/semantic.rs
+++ b/litellm-rust/crates/cache/src/semantic.rs
@@ -4,7 +4,7 @@
 //! `RedisSemanticCache._get_prompt_from_kwargs` (inherited by Valkey) adds Responses API
 //! `input`. Qdrant reads messages only. Each backend picks one of the two extractors here.
 
-use std::{future::Future, io};
+use std::{collections::HashMap, future::Future, io};
 
 use serde::Serialize;
 use serde_json::{
@@ -84,11 +84,35 @@ impl Embedder for PreparedEmbedding {
 }
 
 /// `get_str_from_messages_with_tools`: every message's content text, tool calls and tool results,
-/// then its OpenAI `tool_calls`, then its search results.
+/// then its OpenAI `tool_calls`, then its search results. Each tool result is tagged with the
+/// position of the call it answers.
 pub fn str_from_messages(messages: &[Value]) -> String {
+    let messages: Vec<_> = messages.iter().filter_map(Value::as_object).collect();
+    let call_ordinals = tool_call_ordinals(messages.iter().flat_map(|message| {
+        let block_ids = message
+            .get("content")
+            .and_then(Value::as_array)
+            .into_iter()
+            .flatten()
+            .filter(|block| block.get("type").and_then(Value::as_str) == Some("tool_use"))
+            .filter_map(|block| block.get("id"));
+        let tool_call_ids = message
+            .get("tool_calls")
+            .and_then(Value::as_array)
+            .into_iter()
+            .flatten()
+            .filter_map(|tool_call| tool_call.get("id"));
+        block_ids.chain(tool_call_ids)
+    }));
     let mut text = String::new();
-    for message in messages.iter().filter_map(Value::as_object) {
-        push_content_text(&mut text, message.get("content"));
+    for message in messages {
+        if message.get("role").and_then(Value::as_str) == Some("tool") {
+            text.push_str(&tool_result_tag(
+                message.get("tool_call_id"),
+                &call_ordinals,
+            ));
+        }
+        push_content_text(&mut text, message.get("content"), &call_ordinals);
         if let Some(Value::Array(tool_calls)) = message.get("tool_calls") {
             for tool_call in tool_calls.iter().filter_map(Value::as_object) {
                 let function = tool_call.get("function");
@@ -104,7 +128,11 @@ pub fn str_from_messages(messages: &[Value]) -> String {
 }
 
 /// `_content_str_with_tools`: text parts, Anthropic `tool_use` blocks and `tool_result` content.
-fn push_content_text(text: &mut String, content: Option<&Value>) {
+fn push_content_text(
+    text: &mut String,
+    content: Option<&Value>,
+    call_ordinals: &HashMap<&str, usize>,
+) {
     match content {
         Some(Value::String(content)) => text.push_str(content),
         Some(Value::Array(blocks)) => {
@@ -113,7 +141,10 @@ fn push_content_text(text: &mut String, content: Option<&Value>) {
                     Some("tool_use") => {
                         text.push_str(&tool_call_json(block.get("name"), block.get("input")));
                     }
-                    Some("tool_result") => push_content_text(text, block.get("content")),
+                    Some("tool_result") => {
+                        text.push_str(&tool_result_tag(block.get("tool_use_id"), call_ordinals));
+                        push_content_text(text, block.get("content"), call_ordinals);
+                    }
                     _ => {
                         if let Some(block_text) = block.get("text").and_then(Value::as_str) {
                             text.push_str(block_text);
@@ -126,6 +157,26 @@ fn push_content_text(text: &mut String, content: Option<&Value>) {
     }
 }
 
+/// `tool_call_ordinals`: the 1-based position of each distinct string call id, first seen first.
+fn tool_call_ordinals<'a>(call_ids: impl Iterator<Item = &'a Value>) -> HashMap<&'a str, usize> {
+    let mut ordinals = HashMap::new();
+    for call_id in call_ids.filter_map(Value::as_str) {
+        let next = ordinals.len() + 1;
+        ordinals.entry(call_id).or_insert(next);
+    }
+    ordinals
+}
+
+/// `tool_result_str`: `{"result_of_call":N}` for a result answering a known call, else empty.
+fn tool_result_tag(call_id: Option<&Value>, call_ordinals: &HashMap<&str, usize>) -> String {
+    call_id
+        .and_then(Value::as_str)
+        .and_then(|call_id| call_ordinals.get(call_id))
+        .map_or_else(String::new, |ordinal| {
+            format!("{{\"result_of_call\":{ordinal}}}")
+        })
+}
+
 /// `tool_call_str`: the compact `{"name":...,"arguments":...}` a tool call contributes.
 fn tool_call_json(name: Option<&Value>, arguments: Option<&Value>) -> String {
     compact_json(&json!({
@@ -149,8 +200,16 @@ pub fn prompt_from_context(context: &SemanticCacheContext) -> Option<String> {
         return Some(str_from_messages(messages));
     }
     let input = context.input.as_ref()?;
+    let call_ordinals = tool_call_ordinals(
+        input
+            .as_array()
+            .into_iter()
+            .flatten()
+            .filter(|item| item.get("type").and_then(Value::as_str) == Some("function_call"))
+            .filter_map(|item| item.get("call_id")),
+    );
     let mut parts = Vec::new();
-    collect_input_text(input, &mut parts);
+    collect_input_text(input, &mut parts, &call_ordinals);
     let prompt = python_strip(&parts.join("\n")).to_owned();
     (!prompt.is_empty()).then_some(prompt)
 }
@@ -179,14 +238,18 @@ fn push_search_results_text(text: &mut String, search_results: Option<&Value>) {
     }
 }
 
-fn collect_input_text(value: &Value, parts: &mut Vec<String>) {
+fn collect_input_text(
+    value: &Value,
+    parts: &mut Vec<String>,
+    call_ordinals: &HashMap<&str, usize>,
+) {
     match value {
         Value::String(text) => {
             push_trimmed(text, parts);
         }
         Value::Array(items) => {
             for item in items {
-                collect_input_text(item, parts);
+                collect_input_text(item, parts, call_ordinals);
             }
         }
         Value::Object(map) => {
@@ -194,14 +257,24 @@ fn collect_input_text(value: &Value, parts: &mut Vec<String>) {
                 parts.push(tool_call_json(map.get("name"), map.get("arguments")));
                 return;
             }
+            if map.get("type").and_then(Value::as_str) == Some("function_call_output") {
+                let tag = tool_result_tag(map.get("call_id"), call_ordinals);
+                if !tag.is_empty() {
+                    parts.push(tag);
+                    if let Some(output) = map.get("output") {
+                        collect_input_text(output, parts, call_ordinals);
+                    }
+                    return;
+                }
+            }
             if let Some(content) = map.get("content").filter(|content| !content.is_null()) {
-                collect_input_text(content, parts);
+                collect_input_text(content, parts, call_ordinals);
                 return;
             }
             for key in ["text", "output", "input_text", "output_text"] {
                 match map.get(key) {
                     Some(nested @ Value::Array(_)) => {
-                        collect_input_text(nested, parts);
+                        collect_input_text(nested, parts, call_ordinals);
                         return;
                     }
                     Some(Value::String(text)) if push_trimmed(text, parts) => return,
diff --git a/litellm-rust/crates/cache/tests/semantic.rs b/litellm-rust/crates/cache/tests/semantic.rs
index a29844bc241..7ede4948044 100644
--- a/litellm-rust/crates/cache/tests/semantic.rs
+++ b/litellm-rust/crates/cache/tests/semantic.rs
@@ -133,7 +133,40 @@ fn context(messages: Option<Value>, input: Option<Value>) -> SemanticCacheContex
         ]},
         {"role": "tool", "tool_call_id": "c1", "content": "ok"},
     ]),
-    r#"writing{"name":"write","arguments":"{\"path\": \"a\"}"}{"name":"write","arguments":"{\"path\": \"b\"}"}ok"#,
+    r#"writing{"name":"write","arguments":"{\"path\": \"a\"}"}{"name":"write","arguments":"{\"path\": \"b\"}"}{"result_of_call":1}ok"#,
+)]
+#[case::anthropic_parallel_tool_results_tagged_with_their_call(
+    json!([
+        {"role": "assistant", "content": [
+            {"type": "tool_use", "id": "t1", "name": "Read", "input": {"path": "a"}},
+            {"type": "tool_use", "id": "t2", "name": "Read", "input": {"path": "b"}},
+        ]},
+        {"role": "user", "content": [
+            {"type": "tool_result", "tool_use_id": "t2", "content": "B"},
+            {"type": "tool_result", "tool_use_id": "t1", "content": "A"},
+        ]},
+    ]),
+    r#"{"name":"Read","arguments":{"path":"a"}}{"name":"Read","arguments":{"path":"b"}}{"result_of_call":2}B{"result_of_call":1}A"#,
+)]
+#[case::reused_call_ids_keep_first_position(
+    json!([
+        {"role": "assistant", "content": null, "tool_calls": [
+            {"id": "call_0", "type": "function", "function": {"name": "a", "arguments": "{}"}},
+        ]},
+        {"role": "assistant", "content": null, "tool_calls": [
+            {"id": "call_0", "type": "function", "function": {"name": "b", "arguments": "{}"}},
+            {"id": "call_1", "type": "function", "function": {"name": "c", "arguments": "{}"}},
+        ]},
+        {"role": "tool", "tool_call_id": "call_1", "content": "C"},
+    ]),
+    r#"{"name":"a","arguments":"{}"}{"name":"b","arguments":"{}"}{"name":"c","arguments":"{}"}{"result_of_call":2}C"#,
+)]
+#[case::unknown_call_ids_left_untagged(
+    json!([
+        {"role": "tool", "tool_call_id": "c9", "content": "ok"},
+        {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "t9", "content": "done"}]},
+    ]),
+    "okdone",
 )]
 #[case::malformed_tool_call_entries(
     json!([{"role": "assistant", "content": null, "tool_calls": [{"id": "c1", "type": "function"}, "junk"]}]),
@@ -238,7 +271,7 @@ fn prompt_from_messages_reads_messages_only(
         {"type": "function_call", "call_id": "c1", "name": "write_file", "arguments": "{\"path\":\"a.yaml\"}"},
         {"type": "function_call_output", "call_id": "c1", "output": "ok"},
     ])),
-    Some("update the config\n{\"name\":\"write_file\",\"arguments\":\"{\\\"path\\\":\\\"a.yaml\\\"}\"}\nok"),
+    Some("update the config\n{\"name\":\"write_file\",\"arguments\":\"{\\\"path\\\":\\\"a.yaml\\\"}\"}\n{\"result_of_call\":1}\nok"),
 )]
 #[case::responses_structured_function_call_output(
     None,
@@ -246,7 +279,22 @@ fn prompt_from_messages_reads_messages_only(
         {"type": "function_call", "call_id": "c1", "name": "write_file", "arguments": "{}"},
         {"type": "function_call_output", "call_id": "c1", "output": [{"type": "input_text", "text": "denied"}]},
     ])),
-    Some("{\"name\":\"write_file\",\"arguments\":\"{}\"}\ndenied"),
+    Some("{\"name\":\"write_file\",\"arguments\":\"{}\"}\n{\"result_of_call\":1}\ndenied"),
+)]
+#[case::responses_parallel_outputs_tagged_with_their_call(
+    None,
+    Some(json!([
+        {"type": "function_call", "call_id": "c1", "name": "read", "arguments": "a"},
+        {"type": "function_call", "call_id": "c2", "name": "read", "arguments": "b"},
+        {"type": "function_call_output", "call_id": "c2", "output": "B"},
+        {"type": "function_call_output", "call_id": "c1", "output": "A"},
+    ])),
+    Some("{\"name\":\"read\",\"arguments\":\"a\"}\n{\"name\":\"read\",\"arguments\":\"b\"}\n{\"result_of_call\":2}\nB\n{\"result_of_call\":1}\nA"),
+)]
+#[case::responses_unknown_call_id_output_untagged(
+    None,
+    Some(json!([{"type": "function_call_output", "call_id": "c9", "output": "orphan"}])),
+    Some("orphan"),
 )]
 fn prompt_from_context_matches_python(
     #[case] messages: Option<Value>,
diff --git a/litellm/caching/redis_semantic_cache.py b/litellm/caching/redis_semantic_cache.py
index 9968297f01d..88f5acf026e 100644
--- a/litellm/caching/redis_semantic_cache.py
+++ b/litellm/caching/redis_semantic_cache.py
@@ -22,7 +22,9 @@ from litellm.constants import SEMANTIC_CACHE_EMBEDDING_TIMEOUT_SECONDS
 from litellm.litellm_core_utils.asyncify import asyncify
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     get_str_from_messages_with_tools,
+    tool_call_ordinals,
     tool_call_str,
+    tool_result_str,
 )
 from litellm.types.utils import EmbeddingResponse
 
@@ -269,14 +271,17 @@ class RedisSemanticCache(BaseCache):
         if "input" not in kwargs:
             return None
 
+        responses_input: Final = kwargs.get("input")
         prompt_parts: Final[list[str]] = []
-        cls._collect_responses_input_text(kwargs.get("input"), prompt_parts)
+        cls._collect_responses_input_text(responses_input, prompt_parts, cls._responses_call_ordinals(responses_input))
         prompt: Final = "\n".join(prompt_parts).strip()
         return prompt or None
 
     @classmethod
-    def _collect_responses_input_text(cls, value: object, prompt_parts: list[str]) -> None:
-        value = cls._function_call_as_prompt(cls._coerce_response_input_value(value))
+    def _collect_responses_input_text(
+        cls, value: object, prompt_parts: list[str], call_ordinals: Mapping[str, int]
+    ) -> None:
+        value = cls._function_call_as_prompt(cls._coerce_response_input_value(value), call_ordinals)
         if value is None:
             return
 
@@ -288,21 +293,21 @@ class RedisSemanticCache(BaseCache):
 
         if isinstance(value, (list, tuple)):
             for item in value:
-                cls._collect_responses_input_text(item, prompt_parts)
+                cls._collect_responses_input_text(item, prompt_parts, call_ordinals)
             return
 
         if isinstance(value, dict):
             content = value.get("content")
             if content is not None:
-                cls._collect_responses_input_text(content, prompt_parts)
+                cls._collect_responses_input_text(content, prompt_parts, call_ordinals)
                 return
 
-            cls._collect_responses_text_fields(value, prompt_parts)
+            cls._collect_responses_text_fields(value, prompt_parts, call_ordinals)
             return
 
         content = getattr(value, "content", None)
         if content is not None:
-            cls._collect_responses_input_text(content, prompt_parts)
+            cls._collect_responses_input_text(content, prompt_parts, call_ordinals)
             return
 
         for text_key in ("text", "output", "input_text", "output_text"):
@@ -314,21 +319,38 @@ class RedisSemanticCache(BaseCache):
                     return
 
     @classmethod
-    def _collect_responses_text_fields(cls, value: dict, prompt_parts: list[str]) -> None:
+    def _collect_responses_text_fields(
+        cls, value: dict, prompt_parts: list[str], call_ordinals: Mapping[str, int]
+    ) -> None:
         for text_key in ("text", "output", "input_text", "output_text"):
             text_value = value.get(text_key)
             if isinstance(text_value, (list, tuple)):
-                cls._collect_responses_input_text(text_value, prompt_parts)
+                cls._collect_responses_input_text(text_value, prompt_parts, call_ordinals)
                 return
             if isinstance(text_value, str) and (stripped_text := text_value.strip()):
                 prompt_parts.append(stripped_text)
                 return
 
+    @classmethod
+    def _responses_call_ordinals(cls, responses_input: object) -> Mapping[str, int]:
+        items: Final = responses_input if isinstance(responses_input, (list, tuple)) else ()
+        dumped_items: Final = (cls._coerce_response_input_value(item) for item in items)
+        return tool_call_ordinals(
+            item.get("call_id")
+            for item in dumped_items
+            if isinstance(item, dict) and item.get("type") == "function_call"
+        )
+
     @staticmethod
-    def _function_call_as_prompt(value: object) -> object:
-        if isinstance(value, dict) and value.get("type") == "function_call":
+    def _function_call_as_prompt(value: object, call_ordinals: Mapping[str, int]) -> object:
+        if not isinstance(value, dict):
+            return value
+        if value.get("type") == "function_call":
             return tool_call_str(value.get("name"), value.get("arguments"))
-        return value
+        result_tag: Final = (
+            tool_result_str(value.get("call_id"), call_ordinals) if value.get("type") == "function_call_output" else ""
+        )
+        return (result_tag, value.get("output")) if result_tag else value
 
     @staticmethod
     def _coerce_response_input_value(value: object) -> object:
diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py
index d7fe1849670..dddb9f3b468 100644
--- a/litellm/litellm_core_utils/prompt_templates/common_utils.py
+++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py
@@ -199,42 +199,68 @@ def get_str_from_messages_with_tools(messages: object) -> str:
     """
     ``get_str_from_messages`` that also keeps each conversation's tool calls and tool results, so agent turns
     that differ only in their tool exchange (Anthropic ``tool_use`` / ``tool_result``, OpenAI ``tool_calls``)
-    produce different text
+    produce different text. Each result is tagged with the position of the call it answers, since call ids are
+    random per session
     """
-    return "".join(_message_str_with_tools(message) for message in _str_mappings(messages))
+    message_mappings: Final = tuple(_str_mappings(messages))
+    call_ordinals: Final = tool_call_ordinals(_message_tool_call_ids(message_mappings))
+    return "".join(_message_str_with_tools(message, call_ordinals) for message in message_mappings)
 
 
 def tool_call_str(name: object, arguments: object) -> str:
     return f'{{"name":{_compact_json(name)},"arguments":{_compact_json(arguments)}}}'
 
 
+def tool_result_str(call_id: object, call_ordinals: Mapping[str, int]) -> str:
+    ordinal: Final = call_ordinals.get(call_id) if isinstance(call_id, str) else None
+    return "" if ordinal is None else f'{{"result_of_call":{ordinal}}}'
+
+
+def tool_call_ordinals(call_ids: Iterable[object]) -> Mapping[str, int]:
+    string_ids: Final = (call_id for call_id in call_ids if isinstance(call_id, str))
+    return MappingProxyType({call_id: ordinal for ordinal, call_id in enumerate(dict.fromkeys(string_ids), start=1)})
+
+
 def _compact_json(value: object) -> str:
     return json.dumps(value, separators=(",", ":"), default=str)
 
 
-def _message_str_with_tools(message: Mapping[str, object]) -> str:
+def _message_tool_call_ids(messages: Iterable[Mapping[str, object]]) -> Iterator[object]:
+    for message in messages:
+        yield from (
+            block.get("id") for block in _str_mappings(message.get("content")) if block.get("type") == "tool_use"
+        )
+        yield from (tool_call.get("id") for tool_call in _str_mappings(message.get("tool_calls")))
+
+
+def _message_str_with_tools(message: Mapping[str, object], call_ordinals: Mapping[str, int]) -> str:
+    result_tag: Final = (
+        tool_result_str(message.get("tool_call_id"), call_ordinals) if message.get("role") == "tool" else ""
+    )
     return (
-        _content_str_with_tools(message.get("content"))
+        result_tag
+        + _content_str_with_tools(message.get("content"), call_ordinals)
         + "".join(_openai_tool_call_str(tool_call) for tool_call in _str_mappings(message.get("tool_calls")))
         + extract_search_results_text(message.get("search_results"))
     )
 
 
-def _content_str_with_tools(content: object) -> str:
+def _content_str_with_tools(content: object, call_ordinals: Mapping[str, int]) -> str:
     if isinstance(content, str):
         return content
-    return "".join(_block_str_with_tools(block) for block in _str_mappings(content))
+    return "".join(_block_str_with_tools(block, call_ordinals) for block in _str_mappings(content))
 
 
-def _block_str_with_tools(block: Mapping[str, object]) -> str:
-    match block.get("type"):
-        case "tool_use":
-            return tool_call_str(block.get("name"), block.get("input"))
-        case "tool_result":
-            return _content_str_with_tools(block.get("content"))
-        case _:
-            text: Final = block.get("text")
-            return text if isinstance(text, str) else ""
+def _block_str_with_tools(block: Mapping[str, object], call_ordinals: Mapping[str, int]) -> str:
+    block_type: Final = block.get("type")
+    if block_type == "tool_use":
+        return tool_call_str(block.get("name"), block.get("input"))
+    if block_type == "tool_result":
+        return tool_result_str(block.get("tool_use_id"), call_ordinals) + _content_str_with_tools(
+            block.get("content"), call_ordinals
+        )
+    text: Final = block.get("text")
+    return text if isinstance(text, str) else ""
 
 
 def _openai_tool_call_str(tool_call: Mapping[str, object]) -> str:
diff --git a/tests/integration/caching/test_semantic_cache_tool_turns.py b/tests/integration/caching/test_semantic_cache_tool_turns.py
index 6c9a0b060fc..5d6e6a956a1 100644
--- a/tests/integration/caching/test_semantic_cache_tool_turns.py
+++ b/tests/integration/caching/test_semantic_cache_tool_turns.py
@@ -241,10 +241,13 @@ def test_claude_code_tool_turns_on_messages_are_not_served_the_first_turn_answer
         },
     ]
 
-    answers: Final = _send_turns(semantic_proxy, "/v1/messages", _CLAUDE_MODEL, ([task], list_files, read_file))
+    answers: Final = _send_turns(
+        semantic_proxy, "/v1/messages", _CLAUDE_MODEL, ([task], list_files, read_file, list_files)
+    )
 
-    assert len(set(answers)) == 3, f"a later tool turn replayed an earlier cached answer: {answers}"
-    assert answers == semantic_proxy.peer.answered[-3:], semantic_proxy.peer.answered
+    assert len(set(answers[:3])) == 3, f"a later tool turn replayed an earlier cached answer: {answers}"
+    assert answers[:3] == semantic_proxy.peer.answered[-3:], semantic_proxy.peer.answered
+    assert answers[3] == answers[1], f"a repeated tool turn missed the cache: {answers}"
 
 
 def test_openai_agent_loop_tool_calls_on_chat_completions_are_not_served_a_cached_answer(
@@ -270,8 +273,9 @@ def test_openai_agent_loop_tool_calls_on_chat_completions_are_not_served_a_cache
         ]
 
     answers: Final = _send_turns(
-        semantic_proxy, "/v1/chat/completions", _CHAT_MODEL, (wrote("a.yaml"), wrote("b.yaml"))
+        semantic_proxy, "/v1/chat/completions", _CHAT_MODEL, (wrote("a.yaml"), wrote("b.yaml"), wrote("a.yaml"))
     )
 
-    assert len(set(answers)) == 2, f"a different tool call replayed an earlier cached answer: {answers}"
-    assert answers == semantic_proxy.peer.answered[-2:], semantic_proxy.peer.answered
+    assert len(set(answers[:2])) == 2, f"a different tool call replayed an earlier cached answer: {answers}"
+    assert answers[:2] == semantic_proxy.peer.answered[-2:], semantic_proxy.peer.answered
+    assert answers[2] == answers[0], f"a repeated tool call missed the cache: {answers}"
diff --git a/tests/unit/caching/test_redis_semantic_cache.py b/tests/unit/caching/test_redis_semantic_cache.py
index 38700dce62c..6ca4481648b 100644
--- a/tests/unit/caching/test_redis_semantic_cache.py
+++ b/tests/unit/caching/test_redis_semantic_cache.py
@@ -593,10 +593,10 @@ def test_redis_semantic_cache_prompt_extraction_keeps_tool_turns_distinct():
         ]
 
     assert RedisSemanticCache._get_prompt_from_kwargs(messages=turn("ls")) == (
-        'fix the failing test{"name":"Bash","arguments":{"cmd":"ls"}}ok'
+        'fix the failing test{"name":"Bash","arguments":{"cmd":"ls"}}{"result_of_call":1}ok'
     )
     assert RedisSemanticCache._get_prompt_from_kwargs(messages=turn("pwd")) == (
-        'fix the failing test{"name":"Bash","arguments":{"cmd":"pwd"}}ok'
+        'fix the failing test{"name":"Bash","arguments":{"cmd":"pwd"}}{"result_of_call":1}ok'
     )
 
 
@@ -611,7 +611,9 @@ def test_redis_semantic_cache_prompt_extraction_keeps_responses_function_calls()
         ]
     )
 
-    assert prompt == 'update the config\n{"name":"write_file","arguments":"{\\"path\\":\\"a.yaml\\"}"}\nok'
+    assert prompt == (
+        'update the config\n{"name":"write_file","arguments":"{\\"path\\":\\"a.yaml\\"}"}\n{"result_of_call":1}\nok'
+    )
 
 
 def test_redis_semantic_cache_prompt_extraction_keeps_structured_function_call_outputs():
@@ -631,10 +633,30 @@ def test_redis_semantic_cache_prompt_extraction_keeps_structured_function_call_o
         )
 
     expected_call = '{"name":"write_file","arguments":"{\\"path\\":\\"a.txt\\"}"}'
-    assert prompt_for("wrote 5 bytes") == f"write hello\n{expected_call}\nwrote 5 bytes"
+    assert prompt_for("wrote 5 bytes") == f'write hello\n{expected_call}\n{{"result_of_call":1}}\nwrote 5 bytes'
     assert prompt_for("wrote 5 bytes") != prompt_for("PermissionError")
 
 
+def test_redis_semantic_cache_prompt_extraction_tells_apart_parallel_outputs_answering_different_calls():
+    from litellm.caching.redis_semantic_cache import RedisSemanticCache
+
+    def prompt_for(first_output_call_id: str, second_output_call_id: str) -> str | None:
+        return RedisSemanticCache._get_prompt_from_kwargs(
+            input=[
+                {"type": "function_call", "call_id": "c1", "name": "read", "arguments": "a"},
+                {"type": "function_call", "call_id": "c2", "name": "read", "arguments": "b"},
+                {"type": "function_call_output", "call_id": first_output_call_id, "output": "empty"},
+                {"type": "function_call_output", "call_id": second_output_call_id, "output": "secret"},
+            ]
+        )
+
+    assert prompt_for("c2", "c1") == (
+        '{"name":"read","arguments":"a"}\n{"name":"read","arguments":"b"}\n'
+        '{"result_of_call":2}\nempty\n{"result_of_call":1}\nsecret'
+    )
+    assert prompt_for("c1", "c2") != prompt_for("c2", "c1")
+
+
 def test_redis_semantic_cache_prompt_extraction_handles_model_objects():
     from litellm.caching.redis_semantic_cache import RedisSemanticCache
 
diff --git a/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py b/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
index 4c1af95f4fe..2bd593bea0d 100644
--- a/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
+++ b/tests/unit/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
@@ -7,8 +7,6 @@ from typing import Final
 
 import pytest
 
-from litellm.types.utils import ChatCompletionMessageToolCall, Function, Message
-
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     ENCRYPTED_REASONING_SIGNATURE_PREFIX,
     TOOL_RESULT_IMAGE_BOUNDARY,
@@ -32,6 +30,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
     system_messages_first,
     update_messages_with_model_file_ids,
 )
+from litellm.types.utils import ChatCompletionMessageToolCall, Function, Message
 
 _ARTIFACT_FIELD_PATTERN: Final = r'^(?!__.*__$)[^\p{Cc}\p{Cf}\p{Zl}\p{Zp}"\\./[\]]{1,200}$'
 
@@ -2063,9 +2062,51 @@ _TASK: Final = {"role": "user", "content": "fix the failing test"}
                 {"role": "tool", "tool_call_id": "c1", "content": "ok"},
             ],
             'fix the failing testwriting{"name":"write","arguments":"{\\"path\\": \\"a\\"}"}'
-            '{"name":"write","arguments":"{\\"path\\": \\"b\\"}"}ok',
+            '{"name":"write","arguments":"{\\"path\\": \\"b\\"}"}{"result_of_call":1}ok',
             id="openai-tool-calls-in-order-before-tool-result",
         ),
+        pytest.param(
+            [
+                {
+                    "role": "assistant",
+                    "content": [
+                        {"type": "tool_use", "id": "t1", "name": "Read", "input": {"path": "a"}},
+                        {"type": "tool_use", "id": "t2", "name": "Read", "input": {"path": "b"}},
+                    ],
+                },
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "tool_result", "tool_use_id": "t2", "content": "B"},
+                        {"type": "tool_result", "tool_use_id": "t1", "content": "A"},
+                    ],
+                },
+            ],
+            '{"name":"Read","arguments":{"path":"a"}}{"name":"Read","arguments":{"path":"b"}}'
+            '{"result_of_call":2}B{"result_of_call":1}A',
+            id="anthropic-parallel-tool-results-tagged-with-their-call",
+        ),
+        pytest.param(
+            [
+                {
+                    "role": "assistant",
+                    "content": None,
+                    "tool_calls": [{"id": "call_0", "type": "function", "function": {"name": "a", "arguments": "{}"}}],
+                },
+                {
+                    "role": "assistant",
+                    "content": None,
+                    "tool_calls": [
+                        {"id": "call_0", "type": "function", "function": {"name": "b", "arguments": "{}"}},
+                        {"id": "call_1", "type": "function", "function": {"name": "c", "arguments": "{}"}},
+                    ],
+                },
+                {"role": "tool", "tool_call_id": "call_1", "content": "C"},
+            ],
+            '{"name":"a","arguments":"{}"}{"name":"b","arguments":"{}"}{"name":"c","arguments":"{}"}'
+            '{"result_of_call":2}C',
+            id="reused-call-ids-keep-first-position",
+        ),
         pytest.param(
             [
                 Message(
@@ -2120,3 +2161,35 @@ def test_get_str_from_messages_with_tools_keeps_tool_exchange(messages: list[obj
 )
 def test_get_str_from_messages_with_tools_matches_get_str_from_messages_without_tools(messages: list[object]) -> None:
     assert get_str_from_messages_with_tools(messages) == get_str_from_messages(messages)  # pyright: ignore[reportArgumentType]  # untyped fixtures
+
+
+def _parallel_reads(result_for_a: str, result_for_b: str, *, call_id_prefix: str = "c") -> list[object]:
+    return [
+        {
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [
+                {"id": f"{call_id_prefix}1", "type": "function", "function": {"name": "read", "arguments": '"a"'}},
+                {"id": f"{call_id_prefix}2", "type": "function", "function": {"name": "read", "arguments": '"b"'}},
+            ],
+        },
+        {"role": "tool", "tool_call_id": f"{call_id_prefix}1", "content": result_for_a},
+        {"role": "tool", "tool_call_id": f"{call_id_prefix}2", "content": result_for_b},
+    ]
+
+
+def _results_in_swapped_order(result_for_a: str, result_for_b: str) -> list[object]:
+    call, answer_a, answer_b = _parallel_reads(result_for_a, result_for_b)
+    return [call, answer_b, answer_a]
+
+
+def test_get_str_from_messages_with_tools_tells_apart_parallel_results_answering_different_calls() -> None:
+    assert get_str_from_messages_with_tools(_parallel_reads("empty", "secret")) != get_str_from_messages_with_tools(
+        _results_in_swapped_order("secret", "empty")
+    )
+
+
+def test_get_str_from_messages_with_tools_ignores_call_ids_that_differ_between_sessions() -> None:
+    assert get_str_from_messages_with_tools(
+        _parallel_reads("A", "B", call_id_prefix="toolu_")
+    ) == get_str_from_messages_with_tools(_parallel_reads("A", "B"))