diff --git a/open_notebook/graphs/ask.py b/open_notebook/graphs/ask.py
index 51806ba..74f0ae6 100644
--- a/open_notebook/graphs/ask.py
+++ b/open_notebook/graphs/ask.py
@@ -14,6 +14,7 @@ from open_notebook.domain.notebook import vector_search
 from open_notebook.exceptions import OpenNotebookError
 from open_notebook.utils import clean_thinking_content
 from open_notebook.utils.error_classifier import classify_error
+from open_notebook.utils.text_utils import extract_text_content
 
 
 class SubGraphState(TypedDict):
@@ -65,11 +66,7 @@ async def call_model_with_messages(state: ThreadState, config: RunnableConfig) -
         ai_message = await model.ainvoke(system_prompt)
 
         # Clean the thinking content from the response
-        message_content = (
-            ai_message.content
-            if isinstance(ai_message.content, str)
-            else str(ai_message.content)
-        )
+        message_content = extract_text_content(ai_message.content)
         cleaned_content = clean_thinking_content(message_content)
 
         # Parse the cleaned JSON content
@@ -118,11 +115,7 @@ async def provide_answer(state: SubGraphState, config: RunnableConfig) -> dict:
             max_tokens=2000,
         )
         ai_message = await model.ainvoke(system_prompt)
-        ai_content = (
-            ai_message.content
-            if isinstance(ai_message.content, str)
-            else str(ai_message.content)
-        )
+        ai_content = extract_text_content(ai_message.content)
         return {"answers": [clean_thinking_content(ai_content)]}
     except OpenNotebookError:
         raise
@@ -141,11 +134,7 @@ async def write_final_answer(state: ThreadState, config: RunnableConfig) -> dict
             max_tokens=2000,
         )
         ai_message = await model.ainvoke(system_prompt)
-        final_content = (
-            ai_message.content
-            if isinstance(ai_message.content, str)
-            else str(ai_message.content)
-        )
+        final_content = extract_text_content(ai_message.content)
         return {"final_answer": clean_thinking_content(final_content)}
     except OpenNotebookError:
         raise
diff --git a/open_notebook/graphs/chat.py b/open_notebook/graphs/chat.py
index 34469c4..dced398 100644
--- a/open_notebook/graphs/chat.py
+++ b/open_notebook/graphs/chat.py
@@ -16,6 +16,7 @@ from open_notebook.domain.notebook import Notebook
 from open_notebook.exceptions import OpenNotebookError
 from open_notebook.utils import clean_thinking_content
 from open_notebook.utils.error_classifier import classify_error
+from open_notebook.utils.text_utils import extract_text_content
 
 
 class ThreadState(TypedDict):
@@ -72,11 +73,7 @@ def call_model_with_messages(state: ThreadState, config: RunnableConfig) -> dict
         ai_message = model.invoke(payload)
 
         # Clean thinking content from AI response (e.g., <think>...</think> tags)
-        content = (
-            ai_message.content
-            if isinstance(ai_message.content, str)
-            else str(ai_message.content)
-        )
+        content = extract_text_content(ai_message.content)
         cleaned_content = clean_thinking_content(content)
         cleaned_message = ai_message.model_copy(update={"content": cleaned_content})
 
diff --git a/open_notebook/graphs/prompt.py b/open_notebook/graphs/prompt.py
index 00bc356..cd80d10 100644
--- a/open_notebook/graphs/prompt.py
+++ b/open_notebook/graphs/prompt.py
@@ -7,7 +7,7 @@ from langgraph.graph import END, START, StateGraph
 from typing_extensions import TypedDict
 
 from open_notebook.ai.provision import provision_langchain_model
-from open_notebook.utils.text_utils import clean_thinking_content
+from open_notebook.utils.text_utils import clean_thinking_content, extract_text_content
 
 
 class PatternChainState(TypedDict):
@@ -33,7 +33,7 @@ async def call_model(state: dict, config: RunnableConfig) -> dict:
     response = await chain.ainvoke(payload)
 
     # Clean thinking tags from response (handles extended thinking models)
-    output = clean_thinking_content(str(response.content))
+    output = clean_thinking_content(extract_text_content(response.content))
     return {"output": output}
 
 
diff --git a/open_notebook/graphs/source_chat.py b/open_notebook/graphs/source_chat.py
index 843f605..bccc25e 100644
--- a/open_notebook/graphs/source_chat.py
+++ b/open_notebook/graphs/source_chat.py
@@ -17,6 +17,7 @@ from open_notebook.exceptions import OpenNotebookError
 from open_notebook.utils import clean_thinking_content
 from open_notebook.utils.context_builder import ContextBuilder
 from open_notebook.utils.error_classifier import classify_error
+from open_notebook.utils.text_utils import extract_text_content
 
 
 class SourceChatState(TypedDict):
@@ -172,11 +173,7 @@ def _call_model_with_source_context_inner(
     ai_message = model.invoke(payload)
 
     # Clean thinking content from AI response (e.g., <think>...</think> tags)
-    content = (
-        ai_message.content
-        if isinstance(ai_message.content, str)
-        else str(ai_message.content)
-    )
+    content = extract_text_content(ai_message.content)
     cleaned_content = clean_thinking_content(content)
     cleaned_message = ai_message.model_copy(update={"content": cleaned_content})
 
diff --git a/open_notebook/graphs/transformation.py b/open_notebook/graphs/transformation.py
index 8639a37..65bc526 100644
--- a/open_notebook/graphs/transformation.py
+++ b/open_notebook/graphs/transformation.py
@@ -10,6 +10,7 @@ from open_notebook.domain.transformation import DefaultPrompts, Transformation
 from open_notebook.exceptions import OpenNotebookError
 from open_notebook.utils import clean_thinking_content
 from open_notebook.utils.error_classifier import classify_error
+from open_notebook.utils.text_utils import extract_text_content
 
 
 class TransformationState(TypedDict):
@@ -51,9 +52,7 @@ async def run_transformation(state: dict, config: RunnableConfig) -> dict:
         response = await chain.ainvoke(payload)
 
         # Clean thinking content from the response
-        response_content = (
-            response.content if isinstance(response.content, str) else str(response.content)
-        )
+        response_content = extract_text_content(response.content)
         cleaned_content = clean_thinking_content(response_content)
 
         if source:
diff --git a/open_notebook/utils/text_utils.py b/open_notebook/utils/text_utils.py
index 3846924..ff7ea14 100644
--- a/open_notebook/utils/text_utils.py
+++ b/open_notebook/utils/text_utils.py
@@ -117,3 +117,29 @@ def clean_thinking_content(content: str) -> str:
     """
     _, cleaned_content = parse_thinking_content(content)
     return cleaned_content
+
+
+def extract_text_content(content) -> str:
+    """Extract text from LLM response content.
+
+    Handles both plain string responses and structured content formats
+    (e.g. Gemini's envelope format):
+    [{'type': 'text', 'text': '...', 'extras': {...}}]
+
+    Args:
+        content: The content from an AI message, either a string or a list of parts.
+
+    Returns:
+        The extracted text content as a string.
+    """
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        text_parts = []
+        for part in content:
+            if isinstance(part, dict) and "text" in part:
+                text_parts.append(part["text"])
+            elif isinstance(part, str):
+                text_parts.append(part)
+        return "".join(text_parts)
+    return str(content)
diff --git a/pyproject.toml b/pyproject.toml
index caa3ade..d41cd14 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,7 +36,7 @@ dependencies = [
     "ai-prompter>=0.3,<1",
     "esperanto>=2.19.3,<3",
     "surrealdb>=1.0.4",
-    "podcast-creator>=0.9.1,<1",
+    "podcast-creator>=0.9.4,<1",
     "surreal-commands>=1.3.1,<2",
     "numpy>=2.4.1",
 ]
diff --git a/uv.lock b/uv.lock
index ef336aa..375ad11 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2168,7 +2168,7 @@ requires-dist = [
     { name = "loguru", specifier = ">=0.7.2" },
     { name = "mypy", marker = "extra == 'dev'", specifier = ">=1.11.1" },
     { name = "numpy", specifier = ">=2.4.1" },
-    { name = "podcast-creator", specifier = ">=0.9.1,<1" },
+    { name = "podcast-creator", specifier = ">=0.9.4,<1" },
     { name = "pre-commit", marker = "extra == 'dev'", specifier = ">=4.0.1" },
     { name = "pydantic", specifier = ">=2.9.2" },
     { name = "pytest", marker = "extra == 'dev'", specifier = ">=8.0.0" },
@@ -2519,7 +2519,7 @@ wheels = [
 
 [[package]]
 name = "podcast-creator"
-version = "0.9.1"
+version = "0.9.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "ai-prompter" },
@@ -2535,9 +2535,9 @@ dependencies = [
     { name = "requests" },
     { name = "tiktoken" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/7d/de/f7ee60b502dad23b724d669be31fdeb6a790e306968c2cd6a079388262be/podcast_creator-0.9.1.tar.gz", hash = "sha256:177ae68b18c7efd815e555dcec3c644e541bd053e2c63669fd0a18a008b2f374", size = 470751, upload-time = "2026-02-16T17:58:44.275Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/97/4a/9f23b55659d7d236645593a4b75141837ed88568ba6a6a370b01d97827e6/podcast_creator-0.9.4.tar.gz", hash = "sha256:9e40a77c105d0b02f04a3eef7881a34454ef556fabd8297fe68d50307ca5f926", size = 472357, upload-time = "2026-02-17T20:21:57.257Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/e0/d7/687284d059fc490a19d60af8f07a66b19895e15946e7ced143096d3c5ea0/podcast_creator-0.9.1-py3-none-any.whl", hash = "sha256:e3e513f2aacccd96c15bcab891216ff447568551c4392b3f12575aa0cf0cbeee", size = 74421, upload-time = "2026-02-16T17:58:42.818Z" },
+    { url = "https://files.pythonhosted.org/packages/0c/ac/b331aae683771964f0574189c8dbc1bc0c7b22aca9a376d61c3248180848/podcast_creator-0.9.4-py3-none-any.whl", hash = "sha256:2bd1138cbd1a4deda9da657e7e2b9c8a7d8c0cc43c649506af4837aeb708d46f", size = 74844, upload-time = "2026-02-17T20:21:58.271Z" },
 ]
 
 [[package]]