diff --git a/.gitignore b/.gitignore
index f354bfc..c0918cf 100644
--- a/.gitignore
+++ b/.gitignore
@@ -142,3 +142,4 @@ test_outputs/
 agentfly/data/
 *.ipynb
 
+./*.jpg
\ No newline at end of file
diff --git a/README.md b/README.md
index 4d50bd0..7e73d95 100644
--- a/README.md
+++ b/README.md
@@ -54,11 +54,11 @@ Please refer to [installation.md](docs/start/installation.md) for custmoized ins
 ```python
 # Really small example to build an agent and run
 from agentfly.agents import HFAgent
-from agentfly.tools import calculate
+from agentfly.tools import calculator
 messages = [{"role": "user", "content": "What is the result of 1 + 1?"}]
 agent = HFAgent(
     model_name_or_path="Qwen/Qwen2.5-3B-Instruct",
-    tools=[calculate],
+    tools=[calculator],
     template="qwen2.5",
     backend="async_vllm",
 )
diff --git a/agentfly/agents/__init__.py b/agentfly/agents/__init__.py
index b3d2564..ec8166e 100644
--- a/agentfly/agents/__init__.py
+++ b/agentfly/agents/__init__.py
@@ -2,5 +2,4 @@
 from .specialized.code_agent import CodeAgent
 from .specialized.think_agent import ThinkAgent
 from .specialized.gui_agent import GUIAgent
-from .specialized.hf_agent import HFAgent
-from .templates.utils import process_vision_info, tokenize_conversation, tokenize_conversations
\ No newline at end of file
+from .specialized.hf_agent import HFAgent
\ No newline at end of file
diff --git a/agentfly/agents/agent_base.py b/agentfly/agents/agent_base.py
index 4284e4d..c2685bc 100644
--- a/agentfly/agents/agent_base.py
+++ b/agentfly/agents/agent_base.py
@@ -2,7 +2,7 @@
 from collections import defaultdict
 import json
 from .utils.messages import MessagesList
-from .templates.templates import get_template
+from ..templates.templates import get_template
 from ..__init__ import AGENT_DATA_DIR
 from .llm_backends import (
     AsyncVLLMBackend,
@@ -15,8 +15,7 @@
 from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 import numpy as np
 import torch
-from .templates.utils import tokenize_conversations
-from .templates.vision_processor import is_vision_template
+from ..templates import tokenize_conversations
 from .chain.chain_base import ChainRollout
 import os
 import transformers
diff --git a/agentfly/agents/llm_backends/llm_backends.py b/agentfly/agents/llm_backends/llm_backends.py
index 340e985..72331d2 100644
--- a/agentfly/agents/llm_backends/llm_backends.py
+++ b/agentfly/agents/llm_backends/llm_backends.py
@@ -17,8 +17,7 @@
 from ...utils.verl import pad_tensor_to_rank_size
 from vllm import LLM, AsyncLLMEngine, SamplingParams, AsyncEngineArgs
 import openai
-from ..templates.templates import Chat
-from ..templates.vision_processor import get_processor
+from ...templates import Chat
 import logging
 import PIL
 
diff --git a/agentfly/agents/specialized/openai_agent.py b/agentfly/agents/specialized/openai_agent.py
index ae0f37a..38f725e 100644
--- a/agentfly/agents/specialized/openai_agent.py
+++ b/agentfly/agents/specialized/openai_agent.py
@@ -6,8 +6,8 @@
 from ...tools import answer_qa
 from ...tools.tool_base import tool
 from ..agent_base import BaseAgent
-from ..llm_backend import ClientBackend
-from ..backend_config import ClientConfig
+from ..llm_backends import ClientBackend
+from ..llm_backends.backend_configs import ClientConfig
 from tenacity import retry, wait_random_exponential, stop_after_attempt
 from termcolor import colored
 import json
diff --git a/agentfly/agents/templates/__init__.py b/agentfly/agents/templates/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/agentfly/templates/__init__.py b/agentfly/templates/__init__.py
new file mode 100644
index 0000000..d2b2176
--- /dev/null
+++ b/agentfly/templates/__init__.py
@@ -0,0 +1,10 @@
+from .templates import Template, Chat, get_template, register_template
+from .utils import (
+    process_vision_info,
+    tokenize_conversation,
+    tokenize_conversations,
+    compare_hf_template,
+)
+from .tool_policy import ToolPolicy, JsonFormatter
+from .system_policy import SystemPolicy
+from .global_policy import GlobalPolicy
\ No newline at end of file
diff --git a/agentfly/agents/templates/constants.py b/agentfly/templates/constants.py
similarity index 100%
rename from agentfly/agents/templates/constants.py
rename to agentfly/templates/constants.py
diff --git a/agentfly/templates/global_policy.py b/agentfly/templates/global_policy.py
new file mode 100644
index 0000000..1f3e013
--- /dev/null
+++ b/agentfly/templates/global_policy.py
@@ -0,0 +1,5 @@
+import dataclasses
+
+@dataclasses.dataclass
+class GlobalPolicy:
+    prefix: str = None
diff --git a/agentfly/agents/templates/preprocess.py b/agentfly/templates/preprocess.py
similarity index 100%
rename from agentfly/agents/templates/preprocess.py
rename to agentfly/templates/preprocess.py
diff --git a/agentfly/agents/templates/system_policy.py b/agentfly/templates/system_policy.py
similarity index 100%
rename from agentfly/agents/templates/system_policy.py
rename to agentfly/templates/system_policy.py
diff --git a/agentfly/agents/templates/templates.py b/agentfly/templates/templates.py
similarity index 93%
rename from agentfly/agents/templates/templates.py
rename to agentfly/templates/templates.py
index 6b8d3ea..7e54eff 100644
--- a/agentfly/agents/templates/templates.py
+++ b/agentfly/templates/templates.py
@@ -25,6 +25,7 @@
 from .system_policy import Llama32DateProcessor, SystemPolicy
 from .tool_policy import ToolPolicy
 from .constants import ToolPlacement, Role
+from .global_policy import GlobalPolicy
 
 Logger = logging.getLogger(__name__)
 
@@ -36,15 +37,25 @@
     console_handler.setFormatter(formatter)
     Logger.addHandler(console_handler)
 
-@dataclasses.dataclass
-class GlobalPolicy:
-    prefix: str = None
-
 
 @dataclasses.dataclass
 class Template:
-    """A class that manages prompt templates and keeps all conversation history."""
-    # Properties
+    """Class that holds all the components of a chat template. Convert messages to string prompts, tokenize messages to token ids, and generate jinja-based chat templates.
+
+    Args:
+        name: The name of this template
+        system_template: The system template component
+        system_template_with_tools: The system template with tool usage component
+        system_message: The default system message
+        stop_words: The stop words where the model stops generating (usually EOS token)
+        tool_template: The tool response template component
+        user_template: The user template component
+        user_template_with_tools: The user template with tool usage component
+        assistant_template: The assistant template component
+        global_policy: The global policy, controls the behavior of the template
+        system_policy: The system message policy, controls the behavior of forming the system message
+        tool_policy: The tool policy for the template, controls the behavior of forming tools.
+    """
     # The name of this template
     name: str
     # The template of the system prompt
@@ -142,10 +153,7 @@ def _supports_tool_call(self) -> bool:
             return False
 
     def render(self, messages: List[Dict], tools=None, add_generation_prompt: bool = False) -> str:
-        """Render the template and return
-        1. the final prompt string,
-        2. the list of string *elements* that compose the prompt, and
-        3. the corresponding list of *roles* (used by downstream post-processing).
+        """Render the template.
 
         The heavy lifting is delegated to small, single-purpose helpers so the
         high-level flow is immediately apparent:
@@ -153,6 +161,16 @@ def render(self, messages: List[Dict], tools=None, add_generation_prompt: bool =
             1. _insert_tools              – decide where the tool catalogue lives
             2. _encode_turns              – encode every conversation turn
             3. _maybe_add_generation_prompt – append the generation prefix if requested
+
+        Args:
+            messages: The list of messages
+            tools: The list of tools
+            add_generation_prompt: Whether to add the generation prefix
+
+        Returns:
+            prompt: The final prompt string
+            elements: The list of string *elements* that compose the prompt
+            roles: The corresponding list of *roles* (used by downstream post-processing)
         """
 
         # Step 1 – decide tool placement & clone messages
@@ -173,15 +191,14 @@ def _insert_tools(self, messages: List[Dict], tools):
         """Clone *messages* and compute where (and how) the tool catalogue
         should be injected.
 
-        Returns
-        -------
-        work_messages : List[Dict]
-            A deepcopy of the original *messages* so we never mutate caller data.
-        tools_str : Optional[str]
-            The formatted tool catalogue or *None* if `tools` is falsy.
-        insert_tools_idx : int
-            Index of the *user* message that receives the catalogue, or -1 when
-            no injection is required.
+        Returns:
+            work_messages : List[Dict]
+                A deepcopy of the original *messages* so we never mutate caller data.
+            tools_str : Optional[str]
+                The formatted tool catalogue or *None* if `tools` is falsy.
+            insert_tools_idx : int
+                Index of the *user* message that receives the catalogue, or -1 when
+                no injection is required.
         """
 
         work_messages = deepcopy(messages)
@@ -418,6 +435,19 @@ def _split_assistant_message(self, assistant_message: str) -> List[str]:
 
 
     def encode(self, messages: List[Dict], tokenizer: PreTrainedTokenizer, return_tensors: str = None, tools=None, add_generation_prompt=False, processor=None) -> str:
+        """Encode the messages to token ids.
+
+        Args:
+            messages: The list of messages
+            tokenizer: The tokenizer
+            return_tensors: The return tensors
+            tools: The list of tools
+            add_generation_prompt: Whether to add the generation prefix
+            processor: The processor for vision templates
+        
+        Returns:
+            inputs: The dictionary of input ids, attention mask, labels, and action mask
+        """
         if processor is None and self.supports_vision():
             raise ValueError(f"Processor is required for vision templates: {self.name}")
         
@@ -587,6 +617,11 @@ def get_vision_inputs(self, messages: List[Dict]):
         return vision_inputs
 
     def jinja_template(self) -> str:
+        """Interface for getting the Jinja template.
+
+        Returns:
+            The Jinja template string
+        """
         if self.chat_template:
             return self.chat_template
         else:
@@ -926,6 +961,13 @@ def dict(self):
 
 class Chat:
     def __init__(self, template: str, messages: List[List[str]]=None, tools=None, tokenizer: PreTrainedTokenizer = None):
+        """
+        Args:
+            template: The name of the template to use.
+            messages: The messages to use for the chat.
+            tools: The tools to use for the chat.
+            tokenizer: The tokenizer to use for the chat.
+        """
         self.template = get_template(template)
         self.messages = self.convert_to_hf_format_messages(messages)
         self.tokenizer = tokenizer
@@ -967,10 +1009,21 @@ def convert_to_hf_format_messages(self, messages: Union[List[Dict], Dict[str, Li
         return hf_messages
 
     def set_messages(self, messages: List[Dict]):
+        """Set the messages for the chat."""
         self.messages = self.convert_to_hf_format_messages(messages)
 
     def prompt(self, add_generation_prompt=False, tools=None) -> str:
+        """Get the prompt for the chat.
+
+        Args:
+            add_generation_prompt: Whether to add the generation prompt.
+            tools: The tools to use for the chat.
+
+        Returns:
+            The prompt for the chat.
+        """
         self.flags['add_generation_prompt'] = add_generation_prompt
+        tools = tools or self.tools
         prompt, _, _ = self.template.render(messages=self.messages, tools=tools, add_generation_prompt=add_generation_prompt)
         return prompt
 
@@ -982,13 +1035,32 @@ def vision_inputs(self) -> List[Any]:
         return self.template.get_vision_inputs(self.messages)
 
     def tokenize(self, tokenizer: PreTrainedTokenizer = None, add_generation_prompt=False, tools=None, processor=None) -> List[int]:
+        """Tokenize the messages.
+
+        Args:
+            tokenizer: The tokenizer to use for the chat.
+            add_generation_prompt: Whether to add the generation prompt.
+            tools: The tools to use for the chat.
+            processor: The processor to use for the chat.
+        
+        Returns:
+            inputs (dict): Inputs for helping training.
+                - input_ids
+                - attention_mask
+                - labels
+                - action_mask
+                - multi_modal_inputs
+        """
         if tokenizer is None:
+            if self.tokenizer is None:
+                raise ValueError("Tokenizer is not set. Set it when initializing the chat or pass it as an argument.")
             tokenizer = self.tokenizer
+
         if tools is None:
             tools = self.tools
         return self.template.encode(messages=self.messages, tokenizer=tokenizer, return_tensors="pt", tools=tools, add_generation_prompt=add_generation_prompt, processor=processor)
 
-    def append(self, message: Union[Dict, List[Dict]]):
+    def append(self, message: Union[Dict]):
         self._convert_single_message_to_hf_format(message)
         self.messages.append(message)
 
diff --git a/agentfly/agents/templates/tool_policy.py b/agentfly/templates/tool_policy.py
similarity index 100%
rename from agentfly/agents/templates/tool_policy.py
rename to agentfly/templates/tool_policy.py
diff --git a/agentfly/agents/templates/utils.py b/agentfly/templates/utils.py
similarity index 98%
rename from agentfly/agents/templates/utils.py
rename to agentfly/templates/utils.py
index ab6c07c..441f705 100644
--- a/agentfly/agents/templates/utils.py
+++ b/agentfly/templates/utils.py
@@ -10,10 +10,10 @@
 import re
 import logging
 from .templates import Chat, get_template
-from ... import AGENT_DATA_DIR
+from .. import AGENT_DATA_DIR
 from typing import Any
 from .vision_processor import get_processor
-# Set up logging that won't be overridden by other modules
+
 LOGGER = logging.getLogger(__name__)
 
 ANSI_RE = re.compile(r'\x1b\[[0-9;]*m')   # matches any ANSI color/style code
@@ -269,7 +269,8 @@ def tokenize_conversations(
     concatenated_mm_inputs = {}
     if concatenate_mm_inputs:
         for key in batch_mm_inputs[0].keys():
-            concatenated_mm_inputs[key] = torch.cat([mm_inputs[key] for mm_inputs in batch_mm_inputs if mm_inputs[key] is not None], dim=0)
+            if mm_inputs[key]:
+                concatenated_mm_inputs[key] = torch.cat([mm_inputs[key] for mm_inputs in batch_mm_inputs if mm_inputs[key] is not None], dim=0)
 
     inputs = dict(
         input_ids=batch_input_ids,
diff --git a/agentfly/agents/templates/vision_processor.py b/agentfly/templates/vision_processor.py
similarity index 100%
rename from agentfly/agents/templates/vision_processor.py
rename to agentfly/templates/vision_processor.py
diff --git a/agentfly/tests/unit/agents/templates/test_text_templates_full_align.py b/agentfly/tests/unit/agents/templates/test_text_templates_full_align.py
index 74cf1f3..652ffa4 100644
--- a/agentfly/tests/unit/agents/templates/test_text_templates_full_align.py
+++ b/agentfly/tests/unit/agents/templates/test_text_templates_full_align.py
@@ -8,7 +8,7 @@
 """
 
 
-from .....agents.templates.utils import compare_hf_template
+from .....templates import compare_hf_template
 from transformers import AutoTokenizer
 import pytest
 
diff --git a/agentfly/tools/tool_base.py b/agentfly/tools/tool_base.py
index 9129ffc..97047c2 100644
--- a/agentfly/tools/tool_base.py
+++ b/agentfly/tools/tool_base.py
@@ -13,6 +13,10 @@
 import concurrent.futures
 from ..envs.manager.env_manager import EnvironmentManager
 
+import logging
+
+logger = logging.getLogger(__name__)
+
 # current_env = contextvars.ContextVar("current_env")
 
 class Tool:
@@ -271,7 +275,8 @@ def decorator(func):
         func_name = func.__name__
         final_name = name or func_name
         if name and name != func_name:
-            warnings.warn(f"Tool name {func_name!r} overridden by {name!r}")
+            logger.warning(f"Tool name {func_name!r} overridden by {name!r}")
+            # warnings.warn(f"Tool name {func_name!r} overridden by {name!r}")
 
         signature  = extract_signatures(func)
         docs       = parse_docstring(inspect.getdoc(func))
diff --git a/agentfly/tools/utils/schema.py b/agentfly/tools/utils/schema.py
index 37016ce..2074178 100644
--- a/agentfly/tools/utils/schema.py
+++ b/agentfly/tools/utils/schema.py
@@ -2,6 +2,9 @@
 import inspect
 import warnings
 from copy import deepcopy
+import logging
+
+logger = logging.getLogger(__name__)
 
 def extract_signatures(func):
     sig = inspect.signature(func)
@@ -153,7 +156,7 @@ def validate_schema(name, description, signature, docs):
         else:
             # May be should raise an error
             properties[param]['type'] = "unknown"
-            warnings.warn(f"Parameter {param} has no type in signature or docstring.")
+            logger.warning(f"Parameter {param} has no type in signature or docstring.")
         
         if "default" in signature[param]:
             properties[param]['default'] = signature[param]['default']
diff --git a/docs/api_references/agents/agent.rst b/docs/api_references/agents/agent.rst
index db85c3f..9ed2c3f 100644
--- a/docs/api_references/agents/agent.rst
+++ b/docs/api_references/agents/agent.rst
@@ -11,10 +11,4 @@ The foundation class for all agents in AgentFly:
     :members:
     :show-inheritance:
 
-Chain Generation
-----------------
-
-Base class for chain-based generation:
 
-.. autoclass:: agentfly.agents.chain.chain_base.ChainRollout
-    :members:
diff --git a/docs/api_references/agents/index.rst b/docs/api_references/agents/index.rst
index 23c5f2c..853b2f1 100644
--- a/docs/api_references/agents/index.rst
+++ b/docs/api_references/agents/index.rst
@@ -9,7 +9,7 @@ Overview
 
 AgentFly provides a comprehensive agent system with a base class and specialized implementations for different use cases. All agents inherit from :py:class:`BaseAgent` and support tool calling, chain rollout, and various backends.
 
-Base Agent
+Structure
 ==========
 
 .. toctree::
@@ -17,97 +17,8 @@ Base Agent
 
    agent
    llm_backends
+   rollout
 
-Core Classes
-===========
-
-BaseAgent
----------
-
-The foundation class for all agents in AgentFly:
-
-.. autoclass:: agentfly.agents.agent_base.BaseAgent
-   :members:
-   :show-inheritance:
-   :special-members: __init__
-
-AutoAgent
----------
-
-Factory class for automatic agent creation:
-
-.. autoclass:: agentfly.agents.auto.AutoAgent
-   :members:
-   :show-inheritance:
-
-Specialized Agents
-==================
-
-ReactAgent
-----------
-
-ReAct-style agent for reasoning and tool use:
-
-.. autoclass:: agentfly.agents.react.react_agent.ReactAgent
-   :members:
-   :show-inheritance:
-
-CodeAgent
----------
-
-Specialized agent for code generation and execution:
-
-.. autoclass:: agentfly.agents.specialized.code_agent.CodeAgent
-   :members:
-   :show-inheritance:
-
-ThinkAgent
-----------
-
-Agent that uses thinking steps before taking actions:
-
-.. autoclass:: agentfly.agents.specialized.think_agent.ThinkAgent
-   :members:
-   :show-inheritance:
-
-GUIAgent
----------
-
-Agent for GUI automation tasks:
-
-.. autoclass:: agentfly.agents.specialized.gui_agent.GUIAgent
-   :members:
-   :show-inheritance:
-
-HFAgent
---------
-
-Hugging Face model-based agent:
-
-.. autoclass:: agentfly.agents.specialized.hf_agent.HFAgent
-   :members:
-   :show-inheritance:
-
-OpenAIAgent
------------
-
-OpenAI API-based agent:
-
-.. autoclass:: agentfly.agents.specialized.openai_agent.OpenAIAgent
-   :members:
-   :show-inheritance:
-
-Chain Generation
-===============
-
-ChainRollout
-------------
-
-Base class for chain-based generation:
-
-.. autoclass:: agentfly.agents.chain.chain_base.ChainRollout
-   :members:
-   :show-inheritance:
 
 Usage Examples
 =============
diff --git a/docs/api_references/agents/llm_backends.rst b/docs/api_references/agents/llm_backends.rst
index 8f57918..ef0d7bb 100644
--- a/docs/api_references/agents/llm_backends.rst
+++ b/docs/api_references/agents/llm_backends.rst
@@ -1,27 +1,19 @@
 LLM Backends
-============
+============================
 
 Overview
---------
+-----------------------------
 
 AgentFly supports multiple LLM backends for text generation, each with their own configuration options.
-This module provides configuration classes for different backend types including Transformers, vLLM, Verl, and OpenAI-compatible clients.
+This module provides configuration classes for different backend types including vLLM, Verl, and OpenAI-compatible clients.
+Among them, Verl backend is designed for internal training usage. The Verl backend is the core design that **decouples agent system and rl training**.
 
 Configuration Classes
---------------------
-
-Transformers Backend
-~~~~~~~~~~~~~~~~~~~
-
-Configuration for the Transformers backend using Hugging Face models:
-
-.. autoclass:: agentfly.agents.llm_backends.backend_configs.TransformersConfig
-   :show-inheritance:
-   :special-members: !__init__
+-----------------------------
 
 
 Async VLLM Backend
-~~~~~~~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Configuration for asynchronous vLLM backend with engine arguments:
 
@@ -31,7 +23,7 @@ Configuration for asynchronous vLLM backend with engine arguments:
 
 
 Async Verl Backend
-~~~~~~~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Configuration for asynchronous Verl backend:
 
@@ -40,7 +32,7 @@ Configuration for asynchronous Verl backend:
    :special-members: !__init__
 
 Client Backend
-~~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Configuration for OpenAI-compatible client backends:
 
@@ -49,10 +41,10 @@ Configuration for OpenAI-compatible client backends:
    :special-members: !__init__
 
 Backend Implementations
-----------------------
+------------------------------
 
 Base Backend
-~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Abstract base class for all LLM backends:
 
@@ -60,26 +52,9 @@ Abstract base class for all LLM backends:
    :members:
    :show-inheritance:
 
-Transformers Backend
-~~~~~~~~~~~~~~~~~~~
-
-HuggingFace Transformers implementation for local model inference:
-
-.. autoclass:: agentfly.agents.llm_backends.llm_backends.TransformersBackend
-   :members:
-   :show-inheritance:
-
-VLLM Backend
-~~~~~~~~~~~~
-
-vLLM implementation for high-performance model inference:
-
-.. autoclass:: agentfly.agents.llm_backends.llm_backends.VLLMBackend
-   :members:
-   :show-inheritance:
 
 Async VLLM Backend
-~~~~~~~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Asynchronous vLLM implementation for high-performance model inference:
 
@@ -97,7 +72,7 @@ Asynchronous Verl implementation for distributed model inference:
    :show-inheritance:
 
 Client Backend
-~~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 OpenAI-compatible client backend for remote API inference:
 
@@ -107,13 +82,13 @@ OpenAI-compatible client backend for remote API inference:
 
 
 Usage Examples
---------------
+------------------------------
 
 Backends are designed to work together with agents. Here are examples showing how to configure different backends when creating agents:
 
 
 Async VLLM Backend
-~~~~~~~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 .. code-block:: python
 
diff --git a/docs/api_references/agents/rollout.rst b/docs/api_references/agents/rollout.rst
new file mode 100644
index 0000000..3bfb6dc
--- /dev/null
+++ b/docs/api_references/agents/rollout.rst
@@ -0,0 +1,11 @@
+Rollout
+=======
+
+
+Chain Generation
+----------------
+
+Base class for chain-based generation:
+
+.. autoclass:: agentfly.agents.chain.chain_base.ChainRollout
+    :members:
\ No newline at end of file
diff --git a/docs/features/chat_template/README.md b/docs/api_references/chat_template/README.md
similarity index 100%
rename from docs/features/chat_template/README.md
rename to docs/api_references/chat_template/README.md
diff --git a/docs/features/chat_template/advanced_features.md b/docs/api_references/chat_template/advanced_features.md
similarity index 96%
rename from docs/features/chat_template/advanced_features.md
rename to docs/api_references/chat_template/advanced_features.md
index d4a1bff..cd7ede5 100644
--- a/docs/features/chat_template/advanced_features.md
+++ b/docs/api_references/chat_template/advanced_features.md
@@ -11,7 +11,7 @@ The Chat Template System provides advanced features for fine-grained control ove
 The system supports multiple strategies for where and how tools are integrated into prompts:
 
 ```python
-from agentfly.agents.templates.constants import ToolPlacement
+from agentfly.templates.constants import ToolPlacement
 
 # 1. SYSTEM placement - tools appear in system message
 system_placement = ToolPlacement.SYSTEM
@@ -31,7 +31,7 @@ Different strategies for formatting tool definitions:
 #### JSON Formatters
 
 ```python
-from agentfly.agents.templates.tool_policy import (
+from agentfly.templates.tool_policy import (
     JsonFormatter, JsonMinifiedFormatter, JsonIndentedFormatter, JsonCompactFormatter
 )
 
@@ -65,7 +65,7 @@ yaml_formatter = YamlFormatter()
 #### Custom Formatters
 
 ```python
-from agentfly.agents.templates.tool_policy import ToolFormatter
+from agentfly.templates.tool_policy import ToolFormatter
 
 class CustomToolFormatter(ToolFormatter):
     def format(self, tools):
@@ -101,7 +101,7 @@ custom_tool_policy = ToolPolicy(
 Process tool content before formatting:
 
 ```python
-from agentfly.agents.templates.tool_policy import ToolContentProcessor
+from agentfly.templates.tool_policy import ToolContentProcessor
 
 class ToolFilterProcessor(ToolContentProcessor):
     """Filter tools based on certain criteria"""
@@ -139,7 +139,7 @@ filtered_tool_policy = ToolPolicy(
 Fine-grained control over system message behavior:
 
 ```python
-from agentfly.agents.templates.system_policy import SystemPolicy
+from agentfly.templates.system_policy import SystemPolicy
 
 # Basic system policy
 basic_policy = SystemPolicy(
@@ -170,7 +170,7 @@ Transform system messages before rendering:
 #### Built-in Processors
 
 ```python
-from agentfly.agents.templates.system_policy import Llama32DateProcessor
+from agentfly.templates.system_policy import Llama32DateProcessor
 
 # Llama 3.2 date processor (adds current date)
 llama_date_policy = SystemPolicy(
@@ -183,7 +183,7 @@ llama_date_policy = SystemPolicy(
 #### Custom Content Processors
 
 ```python
-from agentfly.agents.templates.system_policy import SystemContentProcessor
+from agentfly.templates.system_policy import SystemContentProcessor
 
 class EnvironmentAwareProcessor(SystemContentProcessor):
     """Add environment information to system messages"""
diff --git a/docs/features/chat_template/basic_usage.md b/docs/api_references/chat_template/basic_usage.md
similarity index 74%
rename from docs/features/chat_template/basic_usage.md
rename to docs/api_references/chat_template/basic_usage.md
index b376374..38b550b 100644
--- a/docs/features/chat_template/basic_usage.md
+++ b/docs/api_references/chat_template/basic_usage.md
@@ -7,9 +7,7 @@ The Chat Template System provides a simple yet powerful interface for creating a
 ## Importing the System
 
 ```python
-from agentfly.agents.templates import Chat, get_template, Template
-from agentfly.agents.templates.tool_policy import ToolPolicy, JsonFormatter
-from agentfly.agents.templates.system_policy import SystemPolicy
+from agentfly.templates import Chat, get_template, Template, ToolPolicy, JsonFormatter, SystemPolicy
 ```
 
 ## Using Pre-built Templates
@@ -28,6 +26,8 @@ The system comes with several pre-built templates:
 
 ### Basic Template Usage
 
+`Template` is the basic template class, consists of different components and responsible for forming the prompt. While `Chat` is the class we recommand for users to obtain prompts.
+
 ```python
 # Get a pre-built template
 template = get_template("qwen2.5")
@@ -91,12 +91,13 @@ messages_with_image = [
         "role": "user", 
         "content": [
             {"type": "text", "text": "What's in this image?"},
-            {"type": "image", "image": "/path/to/image.jpg"}
+            {"type": "image", "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg"}
         ]
     }
 ]
 
 chat = Chat(template="qwen2.5-vl", messages=messages_with_image)
+prompt = chat.prompt()
 ```
 
 ## Template Operations
@@ -116,13 +117,21 @@ prompt_with_tools = chat.prompt(tools=tools)
 
 ### Tokenization
 
+Use `Chat.tokenize` method to tokenize the messages with the specified chat template.
+
 ```python
+from transformers import AutoTokenizer, AutoProcessor
+
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-VL-3B-Instruct")
+processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-3B-Instruct")
 # Tokenize the conversation
 inputs = chat.tokenize(
     tokenizer=tokenizer,
     add_generation_prompt=True,
+    processor=processor,
     tools=tools
 )
+print(inputs.keys())
 
 # The result includes:
 # - input_ids: Token IDs
@@ -136,12 +145,6 @@ inputs = chat.tokenize(
 ```python
 # Add a single message
 chat.append({"role": "user", "content": "Another question"})
-
-# Add multiple messages
-chat.append([
-    {"role": "user", "content": "Question 1"},
-    {"role": "assistant", "content": "Answer 1"}
-])
 ```
 
 ## Template Configuration
@@ -269,57 +272,3 @@ tools = [
     "content": "Search results: [results here]"
 }
 ```
-
-## Error Handling
-
-### Common Issues
-
-```python
-try:
-    # Get a template that doesn't exist
-    template = get_template("nonexistent")
-except KeyError as e:
-    print(f"Template not found: {e}")
-
-try:
-    # Create chat with invalid template
-    chat = Chat(template="invalid", messages=messages)
-except KeyError as e:
-    print(f"Invalid template: {e}")
-```
-
-### Validation
-
-```python
-# Check if template supports vision
-if template.supports_vision():
-    print("Template supports vision processing")
-
-# Check if template supports tool calls
-if template._supports_tool_call():
-    print("Template supports tool calls")
-```
-
-## Best Practices
-
-### 1. **Template Naming**
-- Use descriptive names that indicate the model and capabilities
-- Include version information when appropriate
-- Use consistent naming conventions
-
-### 2. **Message Structure**
-- Always use the standard role/content format
-- For multi-modal content, use the list format with type specifications
-- Ensure content types match the template's capabilities
-
-### 3. **Tool Integration**
-- Define tools with clear, descriptive names and parameters
-- Use appropriate tool placement strategies for your use case
-- Test tool integration thoroughly before deployment
-
-### 4. **Vision Processing**
-- Use vision-enabled templates for image/video content
-- Ensure proper image formats and sizes
-- Handle vision token expansion appropriately
-
-This basic usage guide should get you started with the Chat Template System. For more advanced features, see the [Advanced Features](./advanced_features.md) and [Vision Templates](./vision_templates.md) sections.
diff --git a/docs/api_references/chat_template/chat.rst b/docs/api_references/chat_template/chat.rst
new file mode 100644
index 0000000..f790ca1
--- /dev/null
+++ b/docs/api_references/chat_template/chat.rst
@@ -0,0 +1,8 @@
+Chat
+======================
+
+
+.. autoclass:: agentfly.templates.Chat
+    :members:
+    :show-inheritance:
+
diff --git a/docs/api_references/chat_template/core_components.md b/docs/api_references/chat_template/core_components.md
new file mode 100644
index 0000000..f367c56
--- /dev/null
+++ b/docs/api_references/chat_template/core_components.md
@@ -0,0 +1,175 @@
+
+<style>
+
+.system {
+  background-color: #cdb4db;
+  border-radius: 6px;
+  padding: 2px 6px;
+}
+.user {
+  background-color: #ffc8dd;
+  border-radius: 6px;
+  padding: 2px 6px;
+}
+.assistant {
+  background-color: #ffafcc;
+  border-radius: 6px;
+  padding: 2px 6px;
+}
+.tool {
+  background-color: #bde0fe;
+  border-radius: 6px;
+  padding: 2px 6px;
+}
+</style>
+
+
+
+
+# Core Components
+
+### Core Chat Template Components
+
+The Chat Template System is inspired by the art of building block toys - where complex structures are created by combining simple, standardized components. We identify some basic components from LLM's chat templates, and use them to form prompts from conversation messages. Below are some basic core compoenents:
+
+`system_template`: Specify how system prompt is formatted in chat template.
+
+`system_template_with_tools`: Specify how tools along with system prompt is formatted in chat template
+
+`user_template`: Specify how user message is formatted in chat template
+
+`assistant_template`: Specify how assistant is formatted in chat template
+
+`tool_template`: Specify how tool response is formatted in chat template
+
+Assume we have the following chat template, and messages
+```
+system_template = f"System: {system_message}\n"
+system_template_with_tools = f"System: {system_message}\n#Tools: {tools}\n"
+user_template = "User: {content}\n"
+assistant_template = "User: {content}\n"
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": "Hi, Can you help me search the information."},
+    {"role": "assistant", "content": "tool call: search tool arguments: related query"}
+    {"role": "tool", "content": "Searched inforamtion..."}
+]
+
+tools = [
+    {
+        "name": "search",
+        "description": "Search the web."
+    }
+]
+```
+
+**Formatted Prompt**
+
+<span class="system"> </span>: formatted system prompt; <span class="user"> </span>: formatted user message; <span class="assistant"> </span>: formatted assistant message; <span class="tool"> </span>: formatted tool message;
+ 
+1. When combined, these create the complete prompt:
+
+<span class="system">System: You are a helpful assistant.</span>
+
+<span class="user">User: Hi, Can you help me search the information.</span>
+
+<span class="assistant">Assistant: tool call: search\ntool arguments: related query</span>
+
+<span class="tool">Tool: Searched inforamtion...</span>
+
+2. When tools are included, the `system_template_with_tools` is used:
+
+<span class="system">System: You are a helpful assistant.
+<br>
+#Tools: [{"name": "search", "description": "Search the web"}]</span>
+
+<span class="user">User: Hi, Can you help me search the information.</span>
+
+<span class="assistant">Assistant: tool call: search\ntool arguments: related query</span>
+
+<span class="tool">Tool: Searched inforamtion...</span>
+
+
+### High-Level Workflow
+
+```
+Messages + Tools → Template Processing → Vision Processing → LLM-Ready Inputs
+```
+
+The system follows a three-step rendering process:
+
+1. **Tool Insertion**: Decide where and how to inject tool definitions
+2. **Turn Encoding**: Convert each conversation turn to its textual representation
+3. **Generation Prompt**: Optionally append generation prefixes
+
+If we tokenize the input messages, the vision processor will do the following steps:
+
+- **Template** → Human-readable prompt with vision tokens
+- **Vision Processor** → Token expansion and multi-modal inputs
+- **Result** → LLM-ready inputs with proper tensor alignment
+
+### Core Class Components
+
+#### Template
+The central class that manages:
+- Message formatting templates
+- Policy configurations
+- Jinja template generation
+
+#### Chat
+Recommended class for user usage:
+- Store and format messages
+- Get formatted prompts
+- Tokenize formatted prompt
+
+### Advanced Features
+
+**1. Register & Obtain Template**
+
+Templates are created and retrieved through a global registry:
+```python
+# Registration
+register_template(Template(name="custom", ...))
+
+# Retrieval
+template = get_template("custom")
+```
+
+**2. Fine-grained Behavior Control**
+
+Three levels of policy control:
+
+1. **Global Policy**: Template-wide settings (e.g., prefix tokens)
+2. **System Policy**: System message behavior and content processing
+3. **Tool Policy**: Tool placement, formatting, and content processing
+
+```python
+# Tool formatting strategies
+JsonFormatter(indent=4)
+JsonCompactFormatter()
+YamlFormatter()
+
+# Tool placement strategies
+ToolPlacement.SYSTEM
+ToolPlacement.FIRST_USER
+ToolPlacement.LAST_USER
+```
+
+**3. Vision Process**
+
+Vision processors are automatically registered when vision tokens are detected:
+```python
+def _register_vision_processor(self):
+    """Automatically register a vision processor for this template"""
+    if self.image_token or self.video_token:
+        # Auto-registration based on template configuration
+```
+
+
+**4. Jinja Template Generation**
+
+Templates can generate HuggingFace-compatible Jinja templates:
+- Enables use with external systems (vLLM, transformers tokenizers, etc.)
+- Maintains consistency between Python and Jinja rendering
+- Supports complex logic through Jinja macros
diff --git a/docs/features/chat_template/custom_templates.md b/docs/api_references/chat_template/custom_templates.md
similarity index 65%
rename from docs/features/chat_template/custom_templates.md
rename to docs/api_references/chat_template/custom_templates.md
index b390515..8ec10c5 100644
--- a/docs/features/chat_template/custom_templates.md
+++ b/docs/api_references/chat_template/custom_templates.md
@@ -8,18 +8,48 @@ The Chat Template System is designed to be highly extensible, allowing you to cr
 
 ### Core Template Fields
 
-```python
-from agentfly.agents.templates import Template
 
-template = Template(
-    name="my-custom-template",           # Unique identifier
-    system_template="{system_message}",  # System message format
-    system_message="Default system message",
-    user_template="{content}",           # User message format
-    assistant_template="{content}",      # Assistant message format
-    tool_template="{observation}",       # Tool response format
-    stop_words=["</s>"]                 # Stop generation tokens
+
+```python
+from agentfly.templates import Template, register_template, Chat
+
+register_template(
+    Template(
+        name="my-custom-template",           # Unique identifier
+        system_template="System: {system_message}",  # System message format
+        system_message="You are a helpful assistant.", # Default system message
+        user_template="User: {content}",           # User message format
+        assistant_template="Assistant: {content}</s>",      # Assistant message format
+        tool_template="Tool: {observation}",       # Tool response format
+        stop_words=["</s>"]                 # Stop generation tokens
+    )
 )
+
+messages = [
+    {"role": "user", "content": "What is the capital of France?"},
+    {"role": "assistant", "content": "The capital of France is Paris."},
+    {"role": "user", "content": "Tell me more about Paris."}
+]
+
+tools = [
+    {
+        "function": {
+            "name": "get_weather",
+            "description": "Get weather information for a city",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "city": {"type": "string", "description": "City name"}
+                },
+                "required": ["city"]
+            }
+        }
+    }
+]
+
+chat = Chat(template="my-custom-template", messages=messages, tools=tools)
+prompt = chat.prompt()
+print(prompt)
 ```
 
 ### Advanced Template Fields
@@ -30,7 +60,6 @@ template = Template(
     
     # Tool support
     system_template_with_tools="System: {system_message}\n\nTools: {tools}",
-    user_template_with_tools="User: {content}\n\nAvailable tools: {tools}",
     
     # Vision support
     vision_start="<vision>",
@@ -48,73 +77,139 @@ template = Template(
 ### 1. Simple Chat Template
 
 ```python
-simple_template = Template(
-    name="simple-chat",
-    system_template="You are a helpful assistant.\n",
-    system_message="You are a helpful assistant.",
-    user_template="User: {content}\n",
-    assistant_template="Assistant: {content}\n",
-    stop_words=["\n"]
+register_template(
+    Template(
+        name="simple-chat",
+        system_template="You are a helpful assistant.\n",
+        system_message="You are a helpful assistant.",
+        user_template="User: {content}\n",
+        assistant_template="Assistant: {content}\n",
+        stop_words=["\n"]
+    )
 )
+chat = Chat(template="simple-chat", messages=messages, tools=tools)
+print(chat.prompt())
 ```
 
 ### 2. XML-Style Template
 
 ```python
-xml_template = Template(
-    name="xml-style",
-    system_template="<system>{system_message}</system>\n",
-    system_message="You are an AI assistant.",
-    user_template="<user>{content}</user>\n",
-    assistant_template="<assistant>{content}</assistant>\n",
-    stop_words=["</assistant>"]
+register_template(
+    Template(
+        name="xml-style",
+        system_template="<system>{system_message}</system>\n",
+        system_message="You are an AI assistant.",
+        user_template="<user>{content}</user>\n",
+        assistant_template="<assistant>{content}</assistant>\n",
+        stop_words=["</assistant>"]
+    )
 )
+chat = Chat(template="xml-style", messages=messages, tools=tools)
+print(chat.prompt())
 ```
 
 ### 3. Markdown-Style Template
 
 ```python
-markdown_template = Template(
-    name="markdown-style",
-    system_template="# System\n{system_message}\n\n",
-    system_message="You are a helpful AI assistant.",
-    user_template="## User\n{content}\n\n",
-    assistant_template="## Assistant\n{content}\n\n",
-    stop_words=["\n\n"]
+register_template(
+    Template(
+        name="markdown-style",
+        system_template="# System\n{system_message}\n\n",
+        system_message="You are a helpful AI assistant.",
+        user_template="## User\n{content}\n\n",
+        assistant_template="## Assistant\n{content}\n\n",
+        stop_words=["\n\n"]
+    )
 )
+chat = Chat(template="markdown-style", messages=messages, tools=tools)
+print(chat.prompt())
 ```
 
 ### 4. Tool-Enabled Template
 
 ```python
-tool_template = Template(
-    name="tool-enabled",
-    system_template="System: {system_message}\n",
-    system_template_with_tools="System: {system_message}\n\nAvailable Tools:\n{tools}\n",
-    system_message="You are an AI assistant with access to tools.",
-    user_template="User: {content}\n",
-    user_template_with_tools="User: {content}\n\nTools: {tools}\n",
-    assistant_template="Assistant: {content}\n",
-    tool_template="Tool Response: {observation}\n",
-    stop_words=["\n"]
+register_template(
+    Template(
+        name="tool-enabled",
+        system_template="System: {system_message}\n",
+        system_template_with_tools="System: {system_message}\n\nAvailable Tools:\n{tools}\n",
+        system_message="You are an AI assistant with access to tools.",
+        user_template="User: {content}\n",
+        user_template_with_tools="User: {content}\n\nTools: {tools}\n",
+        assistant_template="Assistant: {content}\n",
+        tool_template="Tool Response: {observation}\n",
+        stop_words=["\n"]
+    )
 )
+messages = [
+    {"role": "user", "content": "Find me the weather of Paris"},
+    {"role": "assistant", "content": "Tool: get_weather Arguments: {'city': 'Paris'}"},
+    {"role": "Tool", "content": "24 degrees, raining."}
+]
+tools = [
+    {
+        "function": {
+            "name": "get_weather",
+            "description": "Get weather information for a city",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "city": {"type": "string", "description": "City name"}
+                },
+                "required": ["city"]
+            }
+        }
+    }
+]
+chat = Chat(template="tool-enabled", messages=messages, tools=tools)
+print(chat.prompt())
 ```
 
 ### 5. Vision-Enabled Template
 
 ```python
-vision_template = Template(
-    name="vision-enabled",
-    system_template="You are a vision-capable AI assistant.\n",
-    system_message="You are a vision-capable AI assistant.",
-    user_template="User: {content}\n",
-    assistant_template="Assistant: {content}\n",
-    vision_start="<vision>",
-    vision_end="</vision>",
-    image_token="<image>",
-    video_token="<video>",
-    stop_words=["\n"]
+register_template(
+    Template(
+        name="vision-enabled",
+        system_template="You are a vision-capable AI assistant.\n",
+        system_message="You are a vision-capable AI assistant.",
+        user_template="User: {content}\n",
+        assistant_template="Assistant: {content}\n",
+        vision_start="<vision>",
+        vision_end="</vision>",
+        image_token="<image>",
+        video_token="<video>",
+        stop_words=["\n"]
+    )
 )
+
+messages =    [
+    {
+        "role": "system",
+        "content": "You are a multi-modal assistant that can answer questions about images.",
+    },
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "image",
+                "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
+            },
+            {"type": "text", "text": "Describe this image."},
+        ],
+    },
+    {
+        "role": "assistant",
+        "content": [
+            {
+                "type": "text",
+                "text": "The image is a cat.",
+            },
+        ],
+    }
+]
+chat = Chat(template="vision-enabled", messages=messages)
+print(chat.prompt())
 ```
 
 ## Policy Configuration
diff --git a/docs/api_references/chat_template/examples.md b/docs/api_references/chat_template/examples.md
new file mode 100644
index 0000000..d49f031
--- /dev/null
+++ b/docs/api_references/chat_template/examples.md
@@ -0,0 +1,242 @@
+# Examples and Use Cases
+
+## Overview
+
+This section provides comprehensive examples of how to use the Chat Template System in various scenarios. Each example demonstrates different features and capabilities of the system.
+
+## Basic Examples
+
+### Example 1: Simple Chat Template
+
+```python
+from agentfly.templates import Chat, get_template
+
+# Get a pre-built template
+template = get_template("qwen2.5")
+
+# Create a simple conversation
+messages = [
+    {"role": "user", "content": "Hello, how are you?"},
+    {"role": "assistant", "content": "I'm doing well, thank you for asking! How can I help you today?"},
+    {"role": "user", "content": "Can you explain what machine learning is?"}
+]
+
+# Create chat instance
+chat = Chat(template="qwen2.5", messages=messages)
+
+# Generate prompt
+prompt = chat.prompt()
+print("Generated Prompt:")
+print(prompt)
+
+# Generate prompt with generation prompt (for inference)
+prompt_with_gen = chat.prompt(add_generation_prompt=True)
+print("\nPrompt with Generation Prompt:")
+print(prompt_with_gen)
+```
+
+**Output:**
+```
+Generated Prompt:
+<|im_start|>system
+You are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>
+<|im_start|>user
+Hello, how are you?<|im_end|>
+<|im_start|>assistant
+I'm doing well, thank you for asking! How can I help you today?<|im_end|>
+<|im_start|>user
+Can you explain what machine learning is?<|im_end|>
+
+Prompt with Generation Prompt:
+<|im_start|>system
+You are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>
+<|im_start|>user
+Hello, how are you?<|im_end|>
+<|im_start|>assistant
+I'm doing well, thank you for asking! How can I help you today?<|im_end|>
+<|im_start|>user
+Can you explain what machine learning is?<|im_end|>
+<|im_start|>assistant
+```
+
+### Example 2: Chat with Tools
+
+```python
+# Define tools
+tools = [
+    {
+        "function": {
+            "name": "search_web",
+            "description": "Search the web for current information",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "query": {"type": "string", "description": "Search query"},
+                    "max_results": {"type": "integer", "description": "Maximum number of results"}
+                },
+                "required": ["query"]
+            }
+        }
+    },
+    {
+        "function": {
+            "name": "calculate",
+            "description": "Perform mathematical calculations",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "expression": {"type": "string", "description": "Mathematical expression to evaluate"}
+                },
+                "required": ["expression"]
+            }
+        }
+    }
+]
+
+# Create chat with tools
+chat = Chat(template="qwen2.5", messages=messages, tools=tools)
+
+# Generate prompt with tools
+prompt_with_tools = chat.prompt(tools=tools)
+print("Prompt with Tools:")
+print(prompt_with_tools)
+```
+
+**Output:**
+```
+Prompt with Tools:
+<|im_start|>system
+You are Qwen, created by Alibaba Cloud. You are a helpful assistant.
+
+# Tools
+
+You may call one or more functions to assist with the user query.
+
+You are provided with function signatures within <tools></tools> XML tags:
+<tools>
+{"function": {"name": "search_web", "description": "Search the web for current information", "parameters": {"type": "object", "properties": {"query": {"type": "string", "description": "Search query"}, "max_results": {"type": "integer", "description": "Maximum number of results"}, "required": ["query"]}}}
+{"function": {"name": "calculate", "description": "Perform mathematical calculations", "parameters": {"type": "object", "properties": {"expression": {"type": "string", "description": "Mathematical expression to evaluate"}, "required": ["expression"]}}}
+</tools>
+
+<|im_end|>
+<|im_start|>user
+Hello, how are you?<|im_end|>
+<|im_start|>assistant
+I'm doing well, thank you for asking! How can I help you today?<|im_end|>
+<|im_start|>user
+Can you explain what machine learning is?<|im_end|>
+```
+
+### Example 3: Tokenization
+
+```python
+from transformers import AutoTokenizer
+
+# Load tokenizer
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-7B-Instruct")
+
+# Tokenize the conversation
+inputs = chat.tokenize(
+    tokenizer=tokenizer,
+    add_generation_prompt=True,
+    tools=tools
+)
+
+print("Tokenization Results:")
+print(f"Input IDs shape: {inputs['input_ids'].shape}")
+print(f"Attention mask shape: {inputs['attention_mask'].shape}")
+print(f"Labels shape: {inputs['labels'].shape}")
+print(f"Action mask shape: {inputs['action_mask'].shape}")
+
+# Show token alignment
+print(f"\nFirst 20 tokens: {inputs['input_ids'][0][:20]}")
+print(f"First 20 labels: {inputs['labels'][0][:20]}")
+print(f"First 20 action mask: {inputs['action_mask'][0][:20]}")
+```
+
+## Advanced Examples
+
+### Example 4: Custom Template Creation
+
+```python
+from agentfly.templates import Template, register_template
+from agentfly.templates.tool_policy import ToolPolicy, JsonIndentedFormatter
+from agentfly.templates.constants import ToolPlacement
+
+# Create a custom coding assistant template
+coding_template = Template(
+    name="coding-assistant",
+    
+    # System message
+    system_template="""<|im_start|>system
+You are an expert coding assistant. You help users write, debug, and understand code.
+Always provide clear explanations and follow best practices.
+{system_message}<|im_end|>
+""",
+    system_message="You are an expert coding assistant.",
+    
+    # Tool support for code execution
+    system_template_with_tools="""<|im_start|>system
+You are an expert coding assistant with access to code execution tools.
+Always think through the problem before writing code.
+{system_message}
+
+Available Tools:
+{tools}<|im_end|>
+""",
+    
+    # User and assistant templates
+    user_template="<|im_start|>user\n{content}<|im_end|>\n",
+    user_template_with_tools="<|im_start|>user\n{content}\n\nTools: {tools}<|im_end|>\n",
+    assistant_template="<|im_start|>assistant\n{content}<|im_end|>\n",
+    tool_template="<|im_start|>tool\n{observation}<|im_end|>\n",
+    
+    # Stop words
+    stop_words=["<|im_end|>"],
+    
+    # Tool policy - place tools with first user message
+    tool_policy=ToolPolicy(
+        placement=ToolPlacement.FIRST_USER,
+        formatter=JsonIndentedFormatter(indent=2)
+    )
+)
+
+# Register the template
+register_template(coding_template)
+
+# Test the template
+coding_chat = Chat(template="coding-assistant", messages=[
+    {"role": "user", "content": "Write a Python function to calculate fibonacci numbers"}
+])
+
+prompt = coding_chat.prompt()
+print("Coding Assistant Template:")
+print(prompt)
+```
+
+### Example 5: Vision Template Usage
+
+```python
+# Create a vision-enabled chat
+vision_messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "text", "text": "What's in this image? Please describe it in detail."},
+            {"type": "image", "image": "/path/to/sample_image.jpg"}
+        ]
+    }
+]
+
+# Use a vision template
+vision_chat = Chat(template="qwen2.5-vl", messages=vision_messages)
+
+# Generate prompt
+vision_prompt = vision_chat.prompt()
+print("Vision Template Prompt:")
+print(vision_prompt)
+
+# Get vision inputs
+vision_inputs = vision_chat.vision_inputs()
+print(f"\nVision inputs: {list(vision_inputs.keys())}")
+```
diff --git a/docs/features/chat_template/index.rst b/docs/api_references/chat_template/index.rst
similarity index 52%
rename from docs/features/chat_template/index.rst
rename to docs/api_references/chat_template/index.rst
index da7aba2..4cc1a19 100644
--- a/docs/features/chat_template/index.rst
+++ b/docs/api_references/chat_template/index.rst
@@ -1,83 +1,23 @@
 Chat Template System Documentation
-=================================
+=======================================
 
+
+Structure
+---------------------------------------
 .. toctree::
     :maxdepth: 2
-    :hidden:
 
-    architecture
+    core_components
     basic_usage
     custom_templates
     advanced_features
     vision_templates
     examples
-
-Welcome to the comprehensive documentation for the Chat Template System - a powerful and flexible framework for creating conversation templates inspired by building block toys.
-
-Documentation Structure
-------------------------
-
-:doc:`Architecture & Design <architecture>`
-^^^^^^^^^^^^^^^^^^^^
-
-- **System Philosophy**: Building block approach to template design
-- **Architecture Overview**: High-level system design and flow
-- **Design Patterns**: Factory, Strategy, and Observer patterns
-- **Extensibility Points**: How to extend the system
-- **Key Design Decisions**: Rationale behind architectural choices
-
-:doc:`Basic Usage <basic_usage>`
-^^^^^^^^^^^^^^^^^^^
-
-- **Getting Started**: Quick start guide and imports
-- **Pre-built Templates**: Available templates and their usage
-- **Chat Operations**: Creating chats, generating prompts, tokenization
-- **Template Configuration**: Basic template structure and fields
-- **Message Formats**: Standard and multi-modal message structures
-- **Error Handling**: Common issues and validation
-
-:doc:`Custom Templates <custom_templates>`
-^^^^^^^^^^^^^^^^^^^
-
-- **Template Components**: Core and advanced template fields
-- **Template Creation**: Step-by-step template building
-- **Policy Configuration**: System, tool, and global policies
-- **Template Registration**: How to register and manage templates
-- **Advanced Features**: Jinja templates, inheritance, copying
-- **Best Practices**: Template design and testing guidelines
-
-:doc:`Advanced Features <advanced_features>`
-^^^^^^^^^^^^^^^^
-
-- **Tool Policy System**: Placement strategies and formatters
-- **System Policy System**: Message control and content processors
-- **Global Policy Configuration**: Template-wide settings
-- **Policy Composition**: Combining and inheriting policies
-- **Advanced Tool Integration**: Custom placement and validation
-- **Performance Optimization**: Caching and lazy evaluation
-
-:doc:`Vision Templates <vision_templates>`
-^^^^^^^^^^^^^^^
-
-- **Vision Architecture**: Pipeline overview and key components
-- **Creating Vision Templates**: Basic and advanced vision templates
-- **Vision Processor Configuration**: Automatic registration and model inference
-- **Processor Types**: Patch-based, Qwen-VL, LLaVA processors
-- **Input Formats**: Image, video, and message formats
-- **Token Calculation**: Image and video token computation
-- **Advanced Features**: Custom processors and configuration options
-
-:doc:`Examples & Use Cases <examples>`
-^^^^^^^^^^^^^^^^^^^^
-
-- **Basic Examples**: Simple chat, tools, tokenization
-- **Advanced Examples**: Custom templates, vision usage, dynamic generation
-- **Real-World Use Cases**: Customer support, education, content analysis
-- **Testing & Validation**: Template comparison and validation
-- **Complete Examples**: End-to-end implementation examples
+    template
+    chat
 
 Quick Start
------------
+---------------------------------------
 
 .. code-block:: python
 
@@ -166,7 +106,7 @@ Key Features
 Additional Resources
 -----------------------
 
-- **Source Code**: ``agents/agents/agents/templates/``
+- **Source Code**: ``agentfly/templates/``
 - **API Reference**: Check the source code for detailed method documentation
 - **Issues & Discussions**: Use the project's issue tracker for questions
 
@@ -174,8 +114,3 @@ Contributing
 ------------
 
 The template system is designed to be extensible. See :doc:`Custom Templates <custom_templates>` for guidance on adding new template types and processors.
-
----
-
-*This documentation covers the complete Chat Template System. Start with the architecture to understand the design, then follow the usage guides to implement your own templates.*
-
diff --git a/docs/api_references/chat_template/template.rst b/docs/api_references/chat_template/template.rst
new file mode 100644
index 0000000..6c109fb
--- /dev/null
+++ b/docs/api_references/chat_template/template.rst
@@ -0,0 +1,8 @@
+Template
+======================
+
+
+.. autoclass:: agentfly.templates.Template
+    :members:
+    :show-inheritance:
+    :exclude-members: __init__
diff --git a/docs/features/chat_template/vision_templates.md b/docs/api_references/chat_template/vision_templates.md
similarity index 87%
rename from docs/features/chat_template/vision_templates.md
rename to docs/api_references/chat_template/vision_templates.md
index 1635826..76c590b 100644
--- a/docs/features/chat_template/vision_templates.md
+++ b/docs/api_references/chat_template/vision_templates.md
@@ -30,48 +30,83 @@ Messages → Template Processing → Vision Processor → LLM-Ready Inputs
 ### Basic Vision Template
 
 ```python
-from agentfly.agents.templates import Template
-
-vision_template = Template(
-    name="vision-enabled",
-    system_template="You are a vision-capable AI assistant.\n",
-    system_message="You are a vision-capable AI assistant.",
-    user_template="User: {content}\n",
-    assistant_template="Assistant: {content}\n",
-    
-    # Vision configuration
-    vision_start="<|vision_start|>",
-    vision_end="<|vision_end|>",
-    image_token="<|image_pad|>",
-    video_token="<|video_pad|>",
-    
-    stop_words=["\n"]
+from agentfly.templates import Template, register_template
+
+vision_template = register_template(
+    Template(
+        name="vision-enabled",
+        system_template="You are a vision-capable AI assistant.\n",
+        system_message="You are a vision-capable AI assistant.",
+        user_template="User: {content}\n",
+        assistant_template="Assistant: {content}\n",
+        
+        # Vision configuration
+        vision_start="<|vision_start|>",
+        vision_end="<|vision_end|>",
+        image_token="<|image_pad|>",
+        video_token="<|video_pad|>",
+        
+        stop_words=["\n"]
+    )
 )
+
 ```
 
 ### Vision Template with Tools
 
 ```python
-vision_tool_template = Template(
-    name="vision-tool-enabled",
-    system_template="You are a vision-capable AI assistant.\n",
-    system_template_with_tools="You are a vision-capable AI assistant with tools.\n\nTools: {tools}\n",
-    system_message="You are a vision-capable AI assistant with tools.",
-    user_template="User: {content}\n",
-    user_template_with_tools="User: {content}\n\nTools: {tools}\n",
-    assistant_template="Assistant: {content}\n",
-    tool_template="Tool: {observation}\n",
-    
-    # Vision configuration
-    vision_start="<|vision_start|>",
-    vision_end="<|vision_end|>",
-    image_token="<|image_pad|>",
-    video_token="<|video_pad|>",
-    
-    stop_words=["\n"]
+vision_tool_template = register_template(
+    Template(
+        name="vision-tool-enabled",
+        system_template="You are a vision-capable AI assistant.\n",
+        system_template_with_tools="You are a vision-capable AI assistant with tools.\n\nTools: {tools}\n",
+        system_message="You are a vision-capable AI assistant with tools.",
+        user_template="User: {content}\n",
+        user_template_with_tools="User: {content}\n\nTools: {tools}\n",
+        assistant_template="Assistant: {content}\n",
+        tool_template="Tool: {observation}\n",
+        
+        # Vision configuration
+        vision_start="<|vision_start|>",
+        vision_end="<|vision_end|>",
+        image_token="<|image_pad|>",
+        video_token="<|video_pad|>",
+        
+        stop_words=["\n"]
+    )
 )
 ```
 
+### Use the template
+```python
+messages =    [
+    {
+        "role": "system",
+        "content": "You are a multi-modal assistant that can answer questions about images.",
+    },
+    {
+        "role": "user",
+        "content": [
+            {
+                "type": "image",
+                "image": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-VL/assets/demo.jpeg",
+            },
+            {"type": "text", "text": "Describe this image."},
+        ],
+    }
+]
+chat = Chat(template="vision-enabled", messages=messages)
+print(chat.prompt())
+
+# Tokenize the prompt
+from transformers import AutoTokenizer, AutoProcessor
+model_name = "Qwen/Qwen2.5-VL-3B-Instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+processor = AutoProcessor.from_pretrained(model_name)
+inputs = chat.tokenize(tokenizer=tokenizer, processor=processor)
+print(inputs.keys())
+```
+
 ## Vision Processor Configuration
 
 ### Automatic Registration
@@ -558,9 +593,9 @@ config = VisionProcessorConfig(
 Here's a complete example of creating and using a vision template:
 
 ```python
-from agentfly.agents.templates import Template, register_template, Chat
-from agentfly.agents.templates.tool_policy import ToolPolicy, JsonFormatter
-from agentfly.agents.templates.constants import ToolPlacement
+from agentfly.templates import Template, register_template, Chat
+from agentfly.templates.tool_policy import ToolPolicy, JsonFormatter
+from agentfly.templates.constants import ToolPlacement
 
 # Create a comprehensive vision template
 vision_template = Template(
diff --git a/docs/api_references/tools/index.rst b/docs/api_references/tools/index.rst
index 5cccb25..42c3ffb 100644
--- a/docs/api_references/tools/index.rst
+++ b/docs/api_references/tools/index.rst
@@ -1,113 +1,22 @@
-.. _tools_index:
 
-###################
-Tools API Reference
-###################
-
-
-Overview
-========
+Tools
+==============================
 
 AgentFly provides a comprehensive tool system that enables agents to interact with external systems and APIs. Tools can be stateful (with environment management) or stateless, and support both synchronous and asynchronous execution.
 
-Base Tool
-=========
+
+Structure
+-------------------------------
 
 .. toctree::
    :maxdepth: 2
 
    tool
+   predefined_tools
 
-Core Classes
-===========
-
-Tool
-----
-
-The main tool wrapper class:
-
-.. autoclass:: agentfly.tools.tool_base.Tool
-   :members:
-   :show-inheritance:
-   :special-members: __call__
-
-Tool Decorator
--------------
-
-The main decorator for creating tools:
-
-.. autofunction:: agentfly.tools.tool_base.tool
-
-Utility Functions
-================
-
-Tool Registration
-----------------
-
-.. autofunction:: agentfly.tools.register_tool
-
-Tool Retrieval
---------------
-
-.. autofunction:: agentfly.tools.get_tools_from_names
-
-Pre-built Tools
-==============
-
-Code Tools
-----------
-
-.. autofunction:: agentfly.tools.src.code.tools.code_interpreter
-
-Search Tools
-------------
-
-.. autofunction:: agentfly.tools.src.search.google_search.google_search_serper
-
-.. autofunction:: agentfly.tools.src.search.dense_retriever.dense_retrieve
-
-.. autofunction:: agentfly.tools.src.search.async_dense_retriever.asyncdense_retrieve
-
-ALFWorld Tools
---------------
-
-.. autofunction:: agentfly.tools.src.alfworld.tools.alfworld_step
-
-.. autofunction:: agentfly.tools.src.alfworld.tools.alfworld_reset
-
-.. autofunction:: agentfly.tools.src.alfworld.tools.alfworld_get_task_objective
-
-.. autofunction:: agentfly.tools.src.alfworld.tools.alfworld_get_admissible_commands
-
-WebShop Tools
--------------
-
-.. autofunction:: agentfly.tools.src.webshop.tools.webshop_browser
-
-ScienceWorld Tools
-------------------
-
-.. autofunction:: agentfly.tools.src.scienceworld.tools.scienceworld_explorer
-
-ReAct Tools
------------
-
-.. autofunction:: agentfly.tools.src.react.tools.answer_qa
-
-.. autofunction:: agentfly.tools.src.react.tools.answer_math
-
-Utility Tools
--------------
-
-.. autofunction:: agentfly.tools.src.calculate.tools.calculator
-
-.. autofunction:: agentfly.tools.src.ui.tools.pyautogui_code_generator
-
-Usage Examples
-=============
 
 Basic Tool Definition
---------------------
+-------------------------------
 
 .. code-block:: python
 
@@ -139,7 +48,7 @@ Stateful Tool with Environment
        return result
 
 Tool with Schema
----------------
+------------------------------
 
 .. code-block:: python
 
diff --git a/docs/api_references/tools/predefined_tools.rst b/docs/api_references/tools/predefined_tools.rst
new file mode 100644
index 0000000..0bfc086
--- /dev/null
+++ b/docs/api_references/tools/predefined_tools.rst
@@ -0,0 +1,26 @@
+Predefined Tools
+==============================
+
+The following are predefined tool instances that can be used directly with agents.
+
+Code Interpreter
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: agentfly.tools.src.code.tools.code_interpreter
+
+Google Search
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: agentfly.tools.src.search.google_search.google_search_serper
+
+Calculator
+^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: agentfly.tools.src.calculate.tools.calculator
+
+Answer Tools
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. autofunction:: agentfly.tools.src.react.tools.answer_qa
+
+.. autofunction:: agentfly.tools.src.react.tools.answer_math
\ No newline at end of file
diff --git a/docs/api_references/tools/tool.rst b/docs/api_references/tools/tool.rst
index 7d1580e..ac3df5f 100644
--- a/docs/api_references/tools/tool.rst
+++ b/docs/api_references/tools/tool.rst
@@ -1,8 +1,8 @@
 Tool
-==============
+==============================
 
 Base Tool Class
----------------
+------------------------------
 
 The main tool wrapper class:
 
@@ -11,35 +11,9 @@ The main tool wrapper class:
     :special-members: __call__
 
 Tool Decorator
--------------
+------------------------------
 
 The main decorator for creating tools:
 
 .. autofunction:: agentfly.tools.tool_base.tool
 
-Predefined Tools
----------------
-
-The following are predefined tool instances that can be used directly with agents.
-
-Code Interpreter
-^^^^^^^^^^^^^^^
-
-.. autofunction:: agentfly.tools.src.code.tools.code_interpreter
-
-Google Search
-^^^^^^^^^^^^
-
-.. autofunction:: agentfly.tools.src.search.google_search.google_search_serper
-
-Calculator
-^^^^^^^^^^
-
-.. autofunction:: agentfly.tools.src.calculate.tools.calculator
-
-Answer Tools
-^^^^^^^^^^^
-
-.. autofunction:: agentfly.tools.src.react.tools.answer_qa
-
-.. autofunction:: agentfly.tools.src.react.tools.answer_math
diff --git a/docs/features/chat_template/architecture.md b/docs/features/chat_template/architecture.md
deleted file mode 100644
index ea283ad..0000000
--- a/docs/features/chat_template/architecture.md
+++ /dev/null
@@ -1,168 +0,0 @@
-# Architecture & Design Philosophy
-
-## Inspiration: Building Block Toys
-
-The Chat Template System is inspired by the art of building block toys - where complex structures are created by combining simple, standardized components. This philosophy manifests in several key design principles:
-
-### 1. **Modularity**
-Just as building blocks can be snapped together in different configurations, template components are designed to be:
-- **Interchangeable**: Different formatting strategies can be swapped without changing the core logic
-- **Composable**: Complex templates are built from simple, reusable parts
-- **Extensible**: New block types can be added without modifying existing ones
-
-### 2. **Separation of Concerns**
-Each component has a single, well-defined responsibility:
-- **Templates** handle message formatting and structure
-- **Policies** control behavior and configuration
-- **Processors** handle specialized input contents (images, videos, etc.)
-- **Formatters** manage tool representation
-
-### 3. **Strategy Pattern**
-The system uses the strategy pattern extensively, allowing different behaviors to be selected at runtime:
-- **Tool Formatters**: JSON, YAML, custom formats
-- **Tool Placement**: System, first user, last user...
-- **Vision Processors**: Patch-based, model-specific implementations
-
-## System Architecture
-
-### High-Level Flow
-
-```
-Messages + Tools → Template Processing → Vision Processing → LLM-Ready Inputs
-```
-
-The system follows a three-step rendering process:
-
-1. **Tool Insertion**: Decide where and how to inject tool definitions
-2. **Turn Encoding**: Convert each conversation turn to its textual representation
-3. **Generation Prompt**: Optionally append generation prefixes
-
-### Core Components
-
-#### Template Class
-The central orchestrator that manages:
-- Message formatting templates
-- Policy configurations
-- Vision processor registration
-- Jinja template generation
-
-#### Policy System
-Three levels of policy control:
-
-1. **Global Policy**: Template-wide settings (e.g., prefix tokens)
-2. **System Policy**: System message behavior and content processing
-3. **Tool Policy**: Tool placement, formatting, and content processing
-
-#### Vision Processing
-Separate from template processing to maintain clean separation:
-- **Template** → Human-readable prompt with vision tokens
-- **Vision Processor** → Token expansion and multi-modal inputs
-- **Result** → LLM-ready inputs with proper tensor alignment
-
-### Design Patterns
-
-#### Factory Pattern
-Templates are created and retrieved through a global registry:
-```python
-# Registration
-register_template(Template(name="custom", ...))
-
-# Retrieval
-template = get_template("custom")
-```
-
-#### Strategy Pattern
-Different behaviors are encapsulated in strategy classes:
-```python
-# Tool formatting strategies
-JsonFormatter(indent=4)
-JsonCompactFormatter()
-YamlFormatter()
-
-# Tool placement strategies
-ToolPlacement.SYSTEM
-ToolPlacement.FIRST_USER
-ToolPlacement.LAST_USER
-```
-
-#### Observer Pattern
-Vision processors are automatically registered when vision tokens are detected:
-```python
-def _register_vision_processor(self):
-    """Automatically register a vision processor for this template"""
-    if self.image_token or self.video_token:
-        # Auto-registration based on template configuration
-```
-
-## Key Design Decisions
-
-### 1. **Template vs. Processor Separation**
-- **Templates** handle text formatting and structure
-- **Processors** handle specialized input types (images, videos, tools)
-- This separation allows templates to focus on their core responsibility
-
-### 2. **Policy-Based Configuration**
-Instead of hardcoded behavior, templates use configurable policies:
-- **System Policy**: Controls when and how system messages appear
-- **Tool Policy**: Manages tool integration strategy
-- **Global Policy**: Template-wide behavior settings
-
-### 3. **Automatic Vision Registration**
-Vision processors are automatically registered based on template configuration:
-```python
-def __post_init__(self):
-    if self.image_token or self.video_token:
-        self._register_vision_processor()
-```
-
-### 4. **Jinja Template Generation**
-Templates can generate HuggingFace-compatible Jinja templates:
-- Enables use with external systems (vLLM, etc.)
-- Maintains consistency between Python and Jinja rendering
-- Supports complex logic through Jinja macros
-
-## Extensibility Points
-
-### Adding New Template Types
-1. Create a new `Template` instance
-2. Configure templates, policies, and vision settings
-3. Register with `register_template()`
-
-### Adding New Tool Formatters
-1. Inherit from `ToolFormatter` base class
-2. Implement `format()` and `jinja()` methods
-3. Use in `ToolPolicy` configuration
-
-### Adding New Vision Processors
-1. Inherit from `VisionProcessor` base class
-2. Implement required abstract methods
-3. Register with `register_processor()`
-
-### Adding New System Processors
-1. Inherit from `SystemContentProcessor` base class
-2. Implement `__call__()` and `jinja()` methods
-3. Use in `SystemPolicy` configuration
-
-## Benefits of This Architecture
-
-### 1. **Maintainability**
-- Clear separation of concerns
-- Single responsibility principle
-- Easy to modify individual components
-
-### 2. **Flexibility**
-- Multiple strategies for each behavior
-- Runtime configuration through policies
-- Easy to add new capabilities
-
-### 3. **Reusability**
-- Components can be shared across templates
-- Policies can be reused and combined
-- Vision processors work with any template
-
-### 4. **Consistency**
-- Unified interface for all template types
-- Consistent policy configuration
-- Standardized vision processing pipeline
-
-This architecture makes the template system both powerful and easy to use, while maintaining the flexibility to handle diverse use cases and requirements.
diff --git a/docs/features/chat_template/examples.md b/docs/features/chat_template/examples.md
deleted file mode 100644
index dcce310..0000000
--- a/docs/features/chat_template/examples.md
+++ /dev/null
@@ -1,601 +0,0 @@
-# Examples and Use Cases
-
-## Overview
-
-This section provides comprehensive examples of how to use the Chat Template System in various scenarios. Each example demonstrates different features and capabilities of the system.
-
-## Basic Examples
-
-### Example 1: Simple Chat Template
-
-```python
-from agentfly.agents.templates import Chat, get_template
-
-# Get a pre-built template
-template = get_template("qwen2.5")
-
-# Create a simple conversation
-messages = [
-    {"role": "user", "content": "Hello, how are you?"},
-    {"role": "assistant", "content": "I'm doing well, thank you for asking! How can I help you today?"},
-    {"role": "user", "content": "Can you explain what machine learning is?"}
-]
-
-# Create chat instance
-chat = Chat(template="qwen2.5", messages=messages)
-
-# Generate prompt
-prompt = chat.prompt()
-print("Generated Prompt:")
-print(prompt)
-
-# Generate prompt with generation prompt (for inference)
-prompt_with_gen = chat.prompt(add_generation_prompt=True)
-print("\nPrompt with Generation Prompt:")
-print(prompt_with_gen)
-```
-
-**Output:**
-```
-Generated Prompt:
-<|im_start|>system
-You are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>
-<|im_start|>user
-Hello, how are you?<|im_end|>
-<|im_start|>assistant
-I'm doing well, thank you for asking! How can I help you today?<|im_end|>
-<|im_start|>user
-Can you explain what machine learning is?<|im_end|>
-
-Prompt with Generation Prompt:
-<|im_start|>system
-You are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>
-<|im_start|>user
-Hello, how are you?<|im_end|>
-<|im_start|>assistant
-I'm doing well, thank you for asking! How can I help you today?<|im_end|>
-<|im_start|>user
-Can you explain what machine learning is?<|im_end|>
-<|im_start|>assistant
-```
-
-### Example 2: Chat with Tools
-
-```python
-# Define tools
-tools = [
-    {
-        "function": {
-            "name": "search_web",
-            "description": "Search the web for current information",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "query": {"type": "string", "description": "Search query"},
-                    "max_results": {"type": "integer", "description": "Maximum number of results"}
-                },
-                "required": ["query"]
-            }
-        }
-    },
-    {
-        "function": {
-            "name": "calculate",
-            "description": "Perform mathematical calculations",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "expression": {"type": "string", "description": "Mathematical expression to evaluate"}
-                },
-                "required": ["expression"]
-            }
-        }
-    }
-]
-
-# Create chat with tools
-chat = Chat(template="qwen2.5", messages=messages, tools=tools)
-
-# Generate prompt with tools
-prompt_with_tools = chat.prompt(tools=tools)
-print("Prompt with Tools:")
-print(prompt_with_tools)
-```
-
-**Output:**
-```
-Prompt with Tools:
-<|im_start|>system
-You are Qwen, created by Alibaba Cloud. You are a helpful assistant.
-
-# Tools
-
-You may call one or more functions to assist with the user query.
-
-You are provided with function signatures within <tools></tools> XML tags:
-<tools>
-{"function": {"name": "search_web", "description": "Search the web for current information", "parameters": {"type": "object", "properties": {"query": {"type": "string", "description": "Search query"}, "max_results": {"type": "integer", "description": "Maximum number of results"}, "required": ["query"]}}}
-{"function": {"name": "calculate", "description": "Perform mathematical calculations", "parameters": {"type": "object", "properties": {"expression": {"type": "string", "description": "Mathematical expression to evaluate"}, "required": ["expression"]}}}
-</tools>
-
-<|im_end|>
-<|im_start|>user
-Hello, how are you?<|im_end|>
-<|im_start|>assistant
-I'm doing well, thank you for asking! How can I help you today?<|im_end|>
-<|im_start|>user
-Can you explain what machine learning is?<|im_end|>
-```
-
-### Example 3: Tokenization
-
-```python
-from transformers import AutoTokenizer
-
-# Load tokenizer
-tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-7B-Instruct")
-
-# Tokenize the conversation
-inputs = chat.tokenize(
-    tokenizer=tokenizer,
-    add_generation_prompt=True,
-    tools=tools
-)
-
-print("Tokenization Results:")
-print(f"Input IDs shape: {inputs['input_ids'].shape}")
-print(f"Attention mask shape: {inputs['attention_mask'].shape}")
-print(f"Labels shape: {inputs['labels'].shape}")
-print(f"Action mask shape: {inputs['action_mask'].shape}")
-
-# Show token alignment
-print(f"\nFirst 20 tokens: {inputs['input_ids'][0][:20]}")
-print(f"First 20 labels: {inputs['labels'][0][:20]}")
-print(f"First 20 action mask: {inputs['action_mask'][0][:20]}")
-```
-
-## Advanced Examples
-
-### Example 4: Custom Template Creation
-
-```python
-from agentfly.agents.templates import Template, register_template
-from agentfly.agents.templates.tool_policy import ToolPolicy, JsonIndentedFormatter
-from agentfly.agents.templates.constants import ToolPlacement
-
-# Create a custom coding assistant template
-coding_template = Template(
-    name="coding-assistant",
-    
-    # System message
-    system_template="""<|im_start|>system
-You are an expert coding assistant. You help users write, debug, and understand code.
-Always provide clear explanations and follow best practices.
-{system_message}<|im_end|>
-""",
-    system_message="You are an expert coding assistant.",
-    
-    # Tool support for code execution
-    system_template_with_tools="""<|im_start|>system
-You are an expert coding assistant with access to code execution tools.
-Always think through the problem before writing code.
-{system_message}
-
-Available Tools:
-{tools}<|im_end|>
-""",
-    
-    # User and assistant templates
-    user_template="<|im_start|>user\n{content}<|im_end|>\n",
-    user_template_with_tools="<|im_start|>user\n{content}\n\nTools: {tools}<|im_end|>\n",
-    assistant_template="<|im_start|>assistant\n{content}<|im_end|>\n",
-    tool_template="<|im_start|>tool\n{observation}<|im_end|>\n",
-    
-    # Stop words
-    stop_words=["<|im_end|>"],
-    
-    # Tool policy - place tools with first user message
-    tool_policy=ToolPolicy(
-        placement=ToolPlacement.FIRST_USER,
-        formatter=JsonIndentedFormatter(indent=2)
-    )
-)
-
-# Register the template
-register_template(coding_template)
-
-# Test the template
-coding_chat = Chat(template="coding-assistant", messages=[
-    {"role": "user", "content": "Write a Python function to calculate fibonacci numbers"}
-])
-
-prompt = coding_chat.prompt()
-print("Coding Assistant Template:")
-print(prompt)
-```
-
-### Example 5: Vision Template Usage
-
-```python
-# Create a vision-enabled chat
-vision_messages = [
-    {
-        "role": "user",
-        "content": [
-            {"type": "text", "text": "What's in this image? Please describe it in detail."},
-            {"type": "image", "image": "/path/to/sample_image.jpg"}
-        ]
-    }
-]
-
-# Use a vision template
-vision_chat = Chat(template="qwen2.5-vl", messages=vision_messages)
-
-# Generate prompt
-vision_prompt = vision_chat.prompt()
-print("Vision Template Prompt:")
-print(vision_prompt)
-
-# Get vision inputs
-vision_inputs = vision_chat.vision_inputs()
-print(f"\nVision inputs: {list(vision_inputs.keys())}")
-```
-
-### Example 6: Dynamic Template Generation
-
-```python
-def create_specialized_template(base_name, capabilities):
-    """Create template based on capabilities"""
-    
-    # Base templates
-    system_base = "You are a helpful AI assistant."
-    user_base = "User: {content}"
-    assistant_base = "Assistant: {content}"
-    
-    # Add tool support if needed
-    if "tools" in capabilities:
-        system_base += "\n\nYou have access to tools: {tools}"
-        user_base += "\n\nAvailable tools: {tools}"
-    
-    # Add vision support if needed
-    if "vision" in capabilities:
-        system_base += "\n\nYou can process images and videos."
-    
-    return Template(
-        name=f"{base_name}-{'-'.join(capabilities)}",
-        system_template=system_base,
-        user_template=user_base,
-        assistant_template=assistant_base,
-        vision_start="<vision>" if "vision" in capabilities else None,
-        vision_end="</vision>" if "vision" in capabilities else None,
-        image_token="<image>" if "vision" in capabilities else None,
-        video_token="<video>" if "vision" in capabilities else None
-    )
-
-# Create specialized templates
-coding_template = create_specialized_template("coding", ["tools"])
-vision_template = create_specialized_template("vision", ["vision"])
-full_template = create_specialized_template("full", ["tools", "vision"])
-
-# Register them
-register_template(coding_template)
-register_template(vision_template)
-register_template(full_template)
-
-print("Created specialized templates:")
-print(f"- {coding_template.name}")
-print(f"- {vision_template.name}")
-print(f"- {full_template.name}")
-```
-
-## Real-World Use Cases
-
-### Use Case 1: Customer Support Bot
-
-```python
-# Create a customer support template
-support_template = Template(
-    name="customer-support",
-    system_template="""<|im_start|>system
-You are a helpful customer support representative. You help customers with their questions and issues.
-Always be polite, patient, and professional. If you need to escalate an issue, let the customer know.
-{system_message}<|im_end|>
-""",
-    system_message="You are a helpful customer support representative.",
-    
-    # Tool support for looking up customer information
-    system_template_with_tools="""<|im_start|>system
-You are a helpful customer support representative with access to customer databases.
-You can look up customer information and order history to better assist customers.
-{system_message}
-
-Available Tools:
-{tools}<|im_end|>
-""",
-    
-    user_template="<|im_start|>user\n{content}<|im_end|>\n",
-    user_template_with_tools="<|im_start|>user\n{content}\n\nTools: {tools}<|im_end|>\n",
-    assistant_template="<|im_start|>assistant\n{content}<|im_end|>\n",
-    tool_template="<|im_start|>tool\n{observation}<|im_end|>\n",
-    
-    stop_words=["<|im_end|>"],
-    
-    tool_policy=ToolPolicy(
-        placement=ToolPlacement.SYSTEM,
-        formatter=JsonIndentedFormatter(indent=2)
-    )
-)
-
-register_template(support_template)
-
-# Customer support conversation
-support_messages = [
-    {"role": "user", "content": "Hi, I have a question about my recent order #12345"},
-    {"role": "assistant", "content": "Hello! I'd be happy to help you with your order. Let me look up the details for you."}
-]
-
-support_tools = [
-    {
-        "function": {
-            "name": "lookup_order",
-            "description": "Look up order details by order number",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "order_number": {"type": "string", "description": "Order number to look up"}
-                },
-                "required": ["order_number"]
-            }
-        }
-    }
-]
-
-support_chat = Chat(template="customer-support", messages=support_messages, tools=support_tools)
-support_prompt = support_chat.prompt(tools=support_tools)
-print("Customer Support Template:")
-print(support_prompt)
-```
-
-### Use Case 2: Educational Assistant
-
-```python
-# Create an educational assistant template
-education_template = Template(
-    name="education-assistant",
-    system_template="""<|im_start|>system
-You are an educational assistant that helps students learn and understand various subjects.
-Always provide clear explanations, examples, and encourage critical thinking.
-Adapt your explanations to the student's level of understanding.
-{system_message}<|im_end|>
-""",
-    system_message="You are an educational assistant.",
-    
-    # Tool support for educational resources
-    system_template_with_tools="""<|im_start|>system
-You are an educational assistant with access to educational resources and tools.
-You can search for relevant materials, create practice problems, and provide detailed explanations.
-{system_message}
-
-Available Tools:
-{tools}<|im_end|>
-""",
-    
-    user_template="<|im_start|>user\n{content}<|im_end|>\n",
-    user_template_with_tools="<|im_start|>user\n{content}\n\nTools: {tools}<|im_end|>\n",
-    assistant_template="<|im_start|>assistant\n{content}<|im_end|>\n",
-    tool_template="<|im_start|>tool\n{observation}<|im_end|>\n",
-    
-    stop_words=["<|im_end|>"],
-    
-    tool_policy=ToolPolicy(
-        placement=ToolPlacement.FIRST_USER,
-        formatter=JsonIndentedFormatter(indent=2)
-    )
-)
-
-register_template(education_template)
-
-# Educational conversation
-education_messages = [
-    {"role": "user", "content": "Can you explain how photosynthesis works?"}
-]
-
-education_tools = [
-    {
-        "function": {
-            "name": "search_educational_resources",
-            "description": "Search for educational resources on a specific topic",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "topic": {"type": "string", "description": "Topic to search for"},
-                    "grade_level": {"type": "string", "description": "Grade level of the student"}
-                },
-                "required": ["topic"]
-            }
-        }
-    }
-]
-
-education_chat = Chat(template="education-assistant", messages=education_messages, tools=education_tools)
-education_prompt = education_chat.prompt(tools=education_tools)
-print("Educational Assistant Template:")
-print(education_prompt)
-```
-
-### Use Case 3: Multi-Modal Content Analysis
-
-```python
-# Create a multi-modal analysis template
-analysis_template = Template(
-    name="content-analyzer",
-    system_template="""<|im_start|>system
-You are a content analysis expert. You can analyze text, images, and videos to provide insights.
-Always provide detailed analysis with supporting evidence from the content.
-{system_message}<|im_end|>
-""",
-    system_message="You are a content analysis expert.",
-    
-    # Vision support
-    vision_start="<|vision_start|>",
-    vision_end="<|vision_end|>",
-    image_token="<|image_pad|>",
-    video_token="<|video_pad|>",
-    
-    # Tool support for analysis
-    system_template_with_tools="""<|im_start|>system
-You are a content analysis expert with access to analysis tools.
-You can analyze text, images, and videos to provide comprehensive insights.
-{system_message}
-
-Available Tools:
-{tools}<|im_end|>
-""",
-    
-    user_template="<|im_start|>user\n{content}<|im_end|>\n",
-    user_template_with_tools="<|im_start|>user\n{content}\n\nTools: {tools}<|im_end|>\n",
-    assistant_template="<|im_start|>assistant\n{content}<|im_end|>\n",
-    tool_template="<|im_start|>tool\n{observation}<|im_end|>\n",
-    
-    stop_words=["<|im_end|>"],
-    
-    tool_policy=ToolPolicy(
-        placement=ToolPlacement.SYSTEM,
-        formatter=JsonIndentedFormatter(indent=2)
-    )
-)
-
-register_template(analysis_template)
-
-# Multi-modal analysis conversation
-analysis_messages = [
-    {
-        "role": "user",
-        "content": [
-            {"type": "text", "text": "Analyze this image and provide insights about the content, style, and potential use cases."},
-            {"type": "image", "image": "/path/to/analysis_image.jpg"}
-        ]
-    }
-]
-
-analysis_tools = [
-    {
-        "function": {
-            "name": "image_analysis",
-            "description": "Perform detailed image analysis",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "analysis_type": {"type": "string", "enum": ["objects", "text", "emotions", "style"]}
-                },
-                "required": ["analysis_type"]
-            }
-        }
-    }
-]
-
-analysis_chat = Chat(template="content-analyzer", messages=analysis_messages, tools=analysis_tools)
-analysis_prompt = analysis_chat.prompt(tools=analysis_tools)
-print("Content Analyzer Template:")
-print(analysis_prompt)
-```
-
-## Testing and Validation
-
-### Example: Template Comparison
-
-```python
-def compare_templates(template_names, messages, tools=None):
-    """Compare multiple templates side by side"""
-    
-    print("Template Comparison:")
-    print("=" * 80)
-    
-    for template_name in template_names:
-        try:
-            chat = Chat(template=template_name, messages=messages, tools=tools)
-            prompt = chat.prompt(tools=tools)
-            
-            print(f"\n{template_name.upper()}:")
-            print("-" * 40)
-            print(prompt[:200] + "..." if len(prompt) > 200 else prompt)
-            
-        except Exception as e:
-            print(f"\n{template_name.upper()}: ERROR - {e}")
-    
-    print("\n" + "=" * 80)
-
-# Compare different templates
-templates_to_compare = ["qwen2.5", "llama-3.2", "glm-4"]
-test_messages = [
-    {"role": "user", "content": "Hello, how are you?"}
-]
-
-compare_templates(templates_to_compare, test_messages)
-```
-
-### Example: Template Validation
-
-```python
-def validate_template(template_name, test_cases):
-    """Validate a template with various test cases"""
-    
-    print(f"Validating template: {template_name}")
-    print("=" * 60)
-    
-    for i, test_case in enumerate(test_cases, 1):
-        print(f"\nTest Case {i}: {test_case['description']}")
-        print("-" * 40)
-        
-        try:
-            chat = Chat(template=template_name, messages=test_case['messages'])
-            
-            # Test basic prompt generation
-            prompt = chat.prompt()
-            print(f"✓ Basic prompt generated ({len(prompt)} characters)")
-            
-            # Test with tools if provided
-            if 'tools' in test_case:
-                prompt_with_tools = chat.prompt(tools=test_case['tools'])
-                print(f"✓ Tool prompt generated ({len(prompt_with_tools)} characters)")
-            
-            # Test with generation prompt
-            prompt_with_gen = chat.prompt(add_generation_prompt=True)
-            print(f"✓ Generation prompt generated ({len(prompt_with_gen)} characters)")
-            
-        except Exception as e:
-            print(f"✗ Error: {e}")
-    
-    print("\n" + "=" * 60)
-
-# Test cases for validation
-test_cases = [
-    {
-        "description": "Basic conversation",
-        "messages": [
-            {"role": "user", "content": "Hello"},
-            {"role": "assistant", "content": "Hi there!"}
-        ]
-    },
-    {
-        "description": "Conversation with tools",
-        "messages": [
-            {"role": "user", "content": "Search for information"}
-        ],
-        "tools": [
-            {
-                "function": {
-                    "name": "search",
-                    "description": "Search for information",
-                    "parameters": {"type": "object", "properties": {"query": {"type": "string"}}}
-                }
-            }
-        ]
-    }
-]
-
-# Validate a template
-validate_template("qwen2.5", test_cases)
-```
-
-These examples demonstrate the versatility and power of the Chat Template System. Use them as starting points for your own implementations and adapt them to your specific needs.
diff --git a/docs/index.rst b/docs/index.rst
index 4158c90..622cc68 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -176,6 +176,7 @@ Welcome to join our community!
     api_references/tools/index
     api_references/rewards/index
     api_references/environments/index
+    api_references/chat_template/index
 
 .. toctree::
     :maxdepth: 2
diff --git a/docs/start/first_agent.md b/docs/start/first_agent.md
index 9b17ac9..0c8258b 100644
--- a/docs/start/first_agent.md
+++ b/docs/start/first_agent.md
@@ -71,4 +71,14 @@ It is in ShareGPT/OpenAI's input messages, and will look like something to this:
     ]
 }
 ```
+
+To help the training, we can obtain the tokenized trajectories by calling `tokenize_trajectories` method
+```python
+inputs = agent.tokenize_trajectories()
+>>> # 'input_ids': tokenized ids of trajectories
+    # 'attention_mask': attention_mask of ids
+    # 'labels': used for supervised finetuning
+    # 'action_mask': mask where llm generated response are set '1', otherwise '0'
+```
+
 Now we have this built and run the agent. However, to run agent reinforcement learning, we still need several steps: define and get the tool to use, define reward functions, and finally, run the training.
\ No newline at end of file
diff --git a/docs/start/first_tool_reward.md b/docs/start/first_tool_reward.md
index f495fd7..5910251 100644
--- a/docs/start/first_tool_reward.md
+++ b/docs/start/first_tool_reward.md
@@ -34,6 +34,8 @@ Now we have the tool, we can then define the reward function, which also simply
 
 ```python
 from agentfly.rewards import reward
+from typing import List, Dict
+import re
 
 @reward(name="math_reward_string_equal")
 def math_reward_string_equal(prediction: str, answer: str, trajectory: List[Dict]) -> float:
@@ -62,7 +64,7 @@ Now we can use the agent with the reward function we just defined.
 
 ```python
 from agentfly.agents import HFAgent
-from agentfly.tools import calculate
+from agentfly.tools import calculator
 agent = HFAgent(
     model_name_or_path="Qwen/Qwen2.5-3B-Instruct",
     tools=[calculator],
@@ -84,7 +86,7 @@ messages = {
 await agent.run(
     messages=messages,
     max_turns=3,
-    num_chains=1
+    num_chains=5 # Generate 5 trajectories for the query
 )
 ```
 
diff --git a/docs/start/first_training.md b/docs/start/first_training.md
index 245976b..41528ca 100644
--- a/docs/start/first_training.md
+++ b/docs/start/first_training.md
@@ -7,7 +7,7 @@ Finally, we are ready to train the agent.
 
 ----------------
 
-We shw an example of training on GSM8K dataset. First, prepare your training and validation datasets in JSON format. The datasets should follow this structure:
+We show an example of training on GSM8K dataset. First, prepare your training and validation datasets in JSON format. The datasets should follow this structure:
 
 ```
 
@@ -23,7 +23,8 @@ We shw an example of training on GSM8K dataset. First, prepare your training and
     ...
 ]
 ```
-"question" filed is used to put task queries, and will be used to form input messages. While other fileds, in our case, "answer" will be given to the reward function.
+
+We use `question` filed to put task queries, and these "questions" will be used to form input messages. While other fileds, in our case, "answer" will be given to the reward function.
 
 **2. Create Training Script**
 
diff --git a/pyproject.toml b/pyproject.toml
index 129e992..55ca2b0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -70,4 +70,6 @@ docs = [
     "myst-parser",
     "sphinx-markdown-tables",
     "sphinx-rtd-theme",
+    "sphinx-book-theme",
+    "sphinx-design",
 ]