diff --git a/README.md b/README.md
index b9e6f1d..c9e6b4d 100644
--- a/README.md
+++ b/README.md
@@ -42,6 +42,7 @@ In this demo, we showcase how to use DeerFlow to:
 - [❓ FAQ](#faq)
 - [📜 License](#license)
 - [💖 Acknowledgments](#acknowledgments)
+- [⭐ Star History](#star-history)
 
 
 ## Quick Start
@@ -465,3 +466,7 @@ A heartfelt thank you goes out to the core authors of `DeerFlow`, whose vision,
 - **[Henry Li](https://github.com/magiccube/)**
 
 Your unwavering commitment and expertise have been the driving force behind DeerFlow's success. We are honored to have you at the helm of this journey.
+
+## ⭐ Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=bytedance/deer-flow&type=Date)](https://star-history.com/#bytedance/deer-flow&Date)
diff --git a/src/podcast/graph/tts_node.py b/src/podcast/graph/tts_node.py
index 11aeab0..18e49d4 100644
--- a/src/podcast/graph/tts_node.py
+++ b/src/podcast/graph/tts_node.py
@@ -16,9 +16,9 @@ def tts_node(state: PodcastState):
     tts_client = _create_tts_client()
     for line in state["script"].lines:
         tts_client.voice_type = (
-            "BV033_streaming" if line.speaker == "male" else "BV034_streaming"
+            "BV002_streaming" if line.speaker == "male" else "BV001_streaming"
         )
-        result = tts_client.text_to_speech(line.text, speed_ratio=1.05)
+        result = tts_client.text_to_speech(line.paragraph, speed_ratio=1.05)
         if result["success"]:
             audio_data = result["audio_data"]
             audio_chunk = base64.b64decode(audio_data)
diff --git a/src/podcast/types.py b/src/podcast/types.py
index 4e04627..ec1599d 100644
--- a/src/podcast/types.py
+++ b/src/podcast/types.py
@@ -8,7 +8,7 @@ from pydantic import BaseModel, Field
 
 class ScriptLine(BaseModel):
     speaker: Literal["male", "female"] = Field(default="male")
-    text: str = Field(default="")
+    paragraph: str = Field(default="")
 
 
 class Script(BaseModel):
diff --git a/src/prompts/podcast_script_writer.md b/src/prompts/podcast_script_writer.md
index d2d35c8..08762d7 100644
--- a/src/prompts/podcast_script_writer.md
+++ b/src/prompts/podcast_script_writer.md
@@ -11,12 +11,12 @@ You are a professional podcast editor for a show called "Hello Deer." Transform
 
 # Output Format
 
-The output should be formatted as a valid, parseable JSON object of `Script` without "```json":
+The output should be formatted as a valid, parseable JSON object of `Script` without "```json". The `Script` interface is defined as follows:
 
 ```ts
 interface ScriptLine {
   speaker: 'male' | 'female';
-  text: string; // only plain text, never Markdown
+  paragraph: string; // only plain text, never Markdown
 }
 
 interface Script {
@@ -25,51 +25,6 @@ interface Script {
 }
 ```
 
-# Examples
-
-<example>
-{
-  "locale": "en",
-  "lines": [
-    {
-      "speaker": "male",
-      "text": "Hey everyone, welcome to the podcast Hello Deer!"
-    },
-    {
-      "speaker": "female",
-      "text": "Hi there! Today, we’re diving into something super interesting."
-    },
-    {
-      "speaker": "male",
-      "text": "Yeah, we’re talking about [topic]. You know, I’ve been thinking about this a lot lately."
-    },
-    {
-      "speaker": "female",
-      "text": "Oh, me too! It’s such a fascinating subject. So, let’s start with [specific detail or question]."
-    },
-    {
-      "speaker": "male",
-      "text": "Sure! Did you know that [fact or insight]? It’s kind of mind-blowing, right?"
-    },
-    {
-      "speaker": "female",
-      "text": "Totally! And it makes me wonder, what about [related question or thought]?"
-    },
-    {
-      "speaker": "male",
-      "text": "Great point! Actually, [additional detail or answer]."
-    },
-    {
-      "speaker": "female",
-      "text": "Wow, that’s so cool. I didn’t know that! Okay, so what about [next topic or transition]?"
-    },
-    ...
-  ]
-}
-</example>
-
-> Real examples should be **MUCH MUCH LONGER** and more detailed, with placeholders replaced by actual content.
-
 # Notes
 
 - It should always start with "Hello Deer" podcast greetings and followed by topic introduction.