Refine docs

Author: Reason-Wang

agentfly/templates/templates.py

@@ -1023,6 +1023,7 @@ def prompt(self, add_generation_prompt=False, tools=None) -> str:
             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
 
@@ -1043,15 +1044,18 @@ def tokenize(self, tokenizer: PreTrainedTokenizer = None, add_generation_prompt=
             processor: The processor to use for the chat.
         
         Returns:
-            The tokenized messages, a dictionary with the following items:
-            - input_ids
-            - attention_mask
-            - labels
-            - action_mask
-            - multi_modal_inputs
+            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)

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"""

docs/api_references/chat_template/basic_usage.md

@@ -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
@@ -119,12 +120,18 @@ prompt_with_tools = chat.prompt(tools=tools)
 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

docs/api_references/chat_template/core_components.md

@@ -32,7 +32,7 @@
 
 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 system prompt is formatted in chat template.
+`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
 
@@ -72,9 +72,9 @@ tools = [
 
 <span class="system">System: You are a helpful assistant.</span>
 
-<span class="user">User: Hi, how are you today.</span>
+<span class="user">User: Hi, Can you help me search the information.</span>
 
-<span class="assistant">Assistant: I am good. How can I help you?</span>
+<span class="assistant">Assistant: tool call: search\ntool arguments: related query</span>
 
 <span class="tool">Tool: Searched inforamtion...</span>
 
@@ -120,7 +120,7 @@ The central class that manages:
 #### Chat
 Recommended class for user usage:
 - Store and format messages
-- Get formatted prompt
+- Get formatted prompts
 - Tokenize formatted prompt
 
 ### Advanced Features
@@ -170,6 +170,6 @@ def _register_vision_processor(self):
 **4. Jinja Template Generation**
 
 Templates can generate HuggingFace-compatible Jinja templates:
-- Enables use with external systems (vLLM, etc.)
+- Enables use with external systems (vLLM, transformers tokenizers, etc.)
 - Maintains consistency between Python and Jinja rendering
 - Supports complex logic through Jinja macros