fix(llm): strip static prompt from cached Vertex AI requests to preve… (#4321)

skyvern/forge/sdk/api/llm/api_handler_factory.py

@@ -149,6 +149,40 @@ class LLMAPIHandlerFactory:
     _thinking_budget_settings: dict[str, int] | None = None
     _prompt_caching_settings: dict[str, bool] | None = None
 
+    @staticmethod
+    def _strip_static_prompt_from_messages(messages: list[dict[str, Any]], static_prompt: str) -> bool:
+        """
+        Strips the static prompt from the first matching user message in the list.
+        Returns True if the prompt was found and stripped, False otherwise.
+
+        This handles both string content and list-based content (e.g. for vision models).
+        The static prompt is right-stripped to handle trailing newlines from templates.
+        The remaining dynamic content is left-stripped to handle connector whitespace.
+        """
+        static_text = static_prompt.rstrip()
+        prompt_stripped = False
+
+        for msg in messages:
+            if msg.get("role") == "user":
+                content = msg.get("content")
+                if isinstance(content, str):
+                    if content.startswith(static_text):
+                        msg["content"] = content[len(static_text) :].lstrip()
+                        prompt_stripped = True
+                        break
+                elif isinstance(content, list):
+                    for block in content:
+                        if block.get("type") == "text":
+                            text = block.get("text", "")
+                            if text.startswith(static_text):
+                                block["text"] = text[len(static_text) :].lstrip()
+                                prompt_stripped = True
+                                break
+                    if prompt_stripped:
+                        break
+
+        return prompt_stripped
+
     @staticmethod
     def _models_equivalent(left: str | None, right: str | None) -> bool:
         """Used only by `llm_api_handler_with_router_and_fallback`. Router model
@@ -513,6 +547,22 @@ class LLMAPIHandlerFactory:
                 active_params.update(parameters)
                 active_params["cached_content"] = cache_name
                 request_model = active_params.pop("model", primary_model_dict.get("model_name", main_model_group))
+
+                # Clone messages to avoid modifying original list which is needed for fallback
+                active_messages = copy.deepcopy(messages)
+
+                # Strip static prompt from the request messages because it's already in the cache
+                # Sending it again causes double-billing (once cached, once uncached)
+                if context and context.cached_static_prompt:
+                    prompt_stripped = LLMAPIHandlerFactory._strip_static_prompt_from_messages(
+                        active_messages, context.cached_static_prompt
+                    )
+
+                    if prompt_stripped:
+                        LOG.info("Stripped static prompt from cached request to avoid double-billing")
+                    else:
+                        LOG.warning("Could not find static prompt to strip from cached request")
+
                 LOG.info(
                     "Adding Vertex AI cache reference to primary Gemini request",
                     prompt_name=prompt_name,
@@ -525,7 +575,7 @@ class LLMAPIHandlerFactory:
                 request_payload_json = await _log_llm_request_artifact(request_model, True)
                 response = await litellm.acompletion(
                     model=request_model,
-                    messages=messages,
+                    messages=active_messages,
                     timeout=settings.LLM_CONFIG_TIMEOUT,
                     drop_params=True,
                     **active_params,
@@ -913,13 +963,27 @@ class LLMAPIHandlerFactory:
                     **artifact_targets,
                 )
 
+            # Strip static prompt from the request messages because it's already in the cache
+            # Sending it again causes double-billing (once cached, once uncached)
+            active_messages = messages
+            if vertex_cache_attached and context and context.cached_static_prompt:
+                active_messages = copy.deepcopy(messages)
+                prompt_stripped = LLMAPIHandlerFactory._strip_static_prompt_from_messages(
+                    active_messages, context.cached_static_prompt
+                )
+
+                if prompt_stripped:
+                    LOG.info("Stripped static prompt from cached request to avoid double-billing")
+                else:
+                    LOG.warning("Could not find static prompt to strip from cached request")
+
             t_llm_request = time.perf_counter()
             try:
                 # TODO (kerem): add a retry mechanism to this call (acompletion_with_retries)
                 # TODO (kerem): use litellm fallbacks? https://litellm.vercel.app/docs/tutorials/fallbacks#how-does-completion_with_fallbacks-work
                 response = await litellm.acompletion(
                     model=model_name,
-                    messages=messages,
+                    messages=active_messages,
                     drop_params=True,  # Drop unsupported parameters gracefully
                     **active_parameters,
                 )