ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

cursor-chats/20250914_182137_tokens_[.md

@@ -0,0 +1,196 @@
+# Cursor Chat: ai-agent-book
+
+## Metadata
+- **Project**: ai-agent-book
+- **Path**: `/Users/boj`
+- **Date**: 2025-09-14 18:21:37
+- **Session ID**: `416cf8a5-e1f0-4c0c-b740-94784b5fce15`
+
+## Conversation
+
+### 👤 You
+
+"tokens": [
+    " the",
+    " web",
+    "\",",
+    " \"",
+    "parameters",
+    "\":",
+    " {\"",
+    "type",
+    "\":",
+    " \"",
+    "object",
+    "\",",
+    " \"",
+    "properties",
+    "\":",
+    " {\"",
+    "query",
+    "\":",
+    " {\"",
+    "type",
+    "\":",
+
+
+The tokens do not correspond to the actual response.
+
+The output tokens start from:
+    "<|im_start|>",
+    "assistant",
+
+Check how output tokens are recorded in the python main.py code
+
+---
+
+### 🤖 Cursor Assistant
+
+I'll help you check how output tokens are recorded in the attention visualization code. Let me examine the main.py file to understand the token recording mechanism.
+
+---
+
+### 👤 You
+
+"tokens": [
+    " the",
+    " web",
+    "\",",
+    " \"",
+    "parameters",
+    "\":",
+    " {\"",
+    "type",
+    "\":",
+    " \"",
+    "object",
+    "\",",
+    " \"",
+    "properties",
+    "\":",
+    " {\"",
+    "query",
+    "\":",
+    " {\"",
+    "type",
+    "\":",
+
+
+The tokens do not correspond to the actual response.
+
+The output tokens start from:
+    "<|im_start|>",
+    "assistant",
+
+Similarly, the prompt is missing the beginning:
+```
+for information on the web", "parameters": {"type": "object", "properties": {"query": {"type": "string", "description": "Search query"}}, "required": ["query"]}}}
+</tools>
+
+For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
+<tool_call>
+{"name": <function-name>, "arguments": <args-json-object>}
+</tool_call><|im_end|>
+<|im_start|>user
+What's the current time and weather like in Vancouver right now?<|im_end|>
+<|im_start|>assistant
+```
+
+Check how  the input and output tokens are recorded in the python main.py code
+
+---
+
+### 🤖 Cursor Assistant
+
+I'll examine how the input and output tokens are being recorded in your attention visualization code.
+
+---
+
+### 🤖 Cursor Assistant
+
+Now let me check the agent.py file to understand how the tokens are being extracted and recorded in the `generate_with_attention` method:
+
+---
+
+### 🤖 Cursor Assistant
+
+I can see the issue with how tokens are being recorded. The problem occurs because of how the chat template formatting and token extraction interact. Let me examine the specific issue:
+
+---
+
+### 🤖 Cursor Assistant
+
+I've identified the issue with token recording in your attention visualization code. The problem stems from how the chat template formatting interacts with token extraction. Here are the key issues:
+
+## Problems Identified:
+
+1. **Input Token Truncation**: In `main.py` line 421, the input tokens are truncated to the last 100 tokens:
+   ```python
+   all_tokens = traj_data.get('input_tokens', [])[-100:] + traj_data.get('output_tokens', [])
+   ```
+   This causes the beginning of the prompt to be missing.
+
+2. **Chat Template Overhead**: When using `apply_chat_template` with tools, it adds:
+   - System prompts
+   - Tool definitions (which can be very long)
+   - Special tokens (`<|im_start|>`, `<|im_end|>`)
+   - Formatting for the conversation structure
+
+3. **Token Mismatch**: The actual content tokens don't align with what's displayed because the tokenizer includes all the formatting tokens.
+
+## Solution:
+
+Let me fix these issues by modifying how tokens are captured and stored:
+
+---
+
+### 👤 You
+
+Only show the output tokens attention with input+previous output tokens. Do not show attention between input/input tokens
+
+---
+
+### 🤖 Cursor Assistant
+
+I'll modify the attention tracking to only capture attention from output tokens to all previous tokens (input + previously generated outputs), excluding attention between input tokens.
+
+---
+
+### 🤖 Cursor Assistant
+
+Let me check how attention weights are currently captured and modify the code to only track attention from output tokens:
+
+---
+
+### 🤖 Cursor Assistant
+
+Now I'll modify the attention tracking to only capture attention from output tokens (not input-to-input attention):
+
+---
+
+### 🤖 Cursor Assistant
+
+Now let's update the trajectory saving logic to handle the output-only attention format properly:
+
+---
+
+### 🤖 Cursor Assistant
+
+Now let's update the main.py file to handle output-only attention properly:
+
+---
+
+### 🤖 Cursor Assistant
+
+Let me create a test script to verify the output-only attention tracking:
+
+---
+
+### 🤖 Cursor Assistant
+
+Let's now run a quick test with the ReAct agent to confirm the output-only attention works correctly with tool-calling:
+
+---
+
+
+*Exported from [Cursor View](https://github.com/saharmor/cursor-view)*