temp save; temp hold on for rejection sample CoT; try direct RL with raw stepwise data first

.gitignore

@@ -1,5 +1,7 @@
 output/
 result/
 sample/sample_output/
+sample/tmp_dataset_gen/
+sample/output_data/
 
 *__pycache__/

sample/dataset_gen.py

@@ -0,0 +1,263 @@
+import json
+import os
+import re
+import subprocess
+import logging
+import shutil
+
+# --- Configuration ---
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+# File and Directory Paths
+CWD = os.path.dirname(os.path.abspath(__file__))
+FULL_TRACE_PATH = os.path.join(CWD, 'full_trace.jsonl')
+OUTPUT_DIR = os.path.join(CWD, 'output_data')
+FINAL_OUTPUT_PATH = os.path.join(OUTPUT_DIR, 'trace_rl.jsonl')
+PERSISTENT_STATE_FILE = os.path.join(OUTPUT_DIR, 'persistent_state.json')
+TMP_DIR = os.path.join(CWD, 'tmp_dataset_gen')
+
+# --- Swift CLI Configuration ---
+# Make sure to set the OPENAI_API_KEY in your environment variables
+MODEL = "qwen3-8b"
+SWIFT_COMMAND_TEMPLATE = (
+    'swift sample '
+    '--sampler_type distill '
+    '--sampler_engine client '
+    f'--model {MODEL} '
+    '--stream true '
+    '--orm_model external_web_acc '
+    '--dataset "{input_file}" '
+    '--num_return_sequences 1 '
+    '--temperature 0.8 '
+    '--top_p 0.95 '
+    '--external_plugins plugin.py '
+    '--system system_prompt.txt '
+    '--output_dir "{output_dir}" '
+    '--output_file "{output_file}" '
+    '--engine_kwargs \'{{"base_url":"http://192.168.16.116:18088/v1"}}\''
+    # '--engine_kwargs \'{{"base_url":"https://dashscope.aliyuncs.com/compatible-mode/v1"}}\''
+)
+
+
+# --- Constants ---
+MAX_ITERATIONS = 100
+EXIT_PATTERN = re.compile(r'\bexit\(.*\)', re.IGNORECASE)
+
+
+def read_jsonl(file_path):
+    """Reads a .jsonl file and yields each line as a parsed JSON object."""
+    with open(file_path, 'r', encoding='utf-8') as f:
+        for line in f:
+            if line.strip():
+                yield json.loads(line)
+
+
+def write_jsonl(file_path, data, mode='w'):
+    """Writes a list of JSON objects to a .jsonl file."""
+    with open(file_path, mode, encoding='utf-8') as f:
+        for item in data:
+            f.write(json.dumps(item) + '\n')
+
+
+def get_task_id(trace):
+    """Extracts the task ID from the first user message of a trace."""
+    try:
+        match = re.search(r'\[#(\d+)\]', trace['messages'][0]['content'])
+        if match:
+            return match.group(1)
+    except (KeyError, IndexError, TypeError):
+        pass
+    logging.warning(f"Could not find task ID in trace: {trace}")
+    return None
+
+def is_exit_action(trace):
+    """Checks if the last assistant message is an exit action."""
+    try:
+        last_message = trace['messages'][-1]
+        if last_message['role'] == 'assistant':
+            return bool(EXIT_PATTERN.search(last_message['content']))
+    except (KeyError, IndexError, TypeError):
+        pass
+    return False
+
+
+def save_state(b_set, original_traces_map):
+    """Saves the current state (B set and original traces) to a file."""
+    state = {
+        'b_set': b_set,
+        'original_traces_map': original_traces_map
+    }
+    with open(PERSISTENT_STATE_FILE, 'w', encoding='utf-8') as f:
+        json.dump(state, f, indent=4)
+    logging.info(f"Successfully saved state to {PERSISTENT_STATE_FILE}")
+
+
+def load_state():
+    """Loads the state from a file if it exists."""
+    if os.path.exists(PERSISTENT_STATE_FILE):
+        logging.info(f"Found persistent state file. Resuming from {PERSISTENT_STATE_FILE}")
+        with open(PERSISTENT_STATE_FILE, 'r', encoding='utf-8') as f:
+            state = json.load(f)
+            return state['b_set'], state['original_traces_map']
+    return None, None
+
+
+def main():
+    """Main function to generate the dataset."""
+    if not os.path.exists(FULL_TRACE_PATH):
+        logging.error(f"Source file not found: {FULL_TRACE_PATH}")
+        return
+
+    # Create output and temporary directories
+    os.makedirs(OUTPUT_DIR, exist_ok=True)
+    os.makedirs(TMP_DIR, exist_ok=True)
+
+    b_set_to_process, original_traces_map = load_state()
+
+    if b_set_to_process is None:
+        logging.info("No persistent state found. Starting from scratch.")
+        # Initial run: Load full traces and create initial sets A and B
+        original_traces_map = {}
+        initial_a_set = []
+
+        logging.info(f"Reading full traces from {FULL_TRACE_PATH}")
+        for trace in read_jsonl(FULL_TRACE_PATH):
+            task_id = get_task_id(trace)
+            if task_id:
+                original_traces_map[task_id] = trace['messages']
+                if len(trace['messages']) >= 3:
+                    initial_sub_trace = {"messages": trace['messages'][:3]}
+                    initial_a_set.append(initial_sub_trace)
+
+        # Write all of set A to the final RL training data file
+        logging.info(f"Adding {len(initial_a_set)} initial traces to {FINAL_OUTPUT_PATH}")
+        write_jsonl(FINAL_OUTPUT_PATH, initial_a_set, mode='a')
+
+        # Create initial B set from non-exit traces in A
+        b_set_to_process = [trace for trace in initial_a_set if not is_exit_action(trace)]
+        logging.info(f"Created initial B set with {len(b_set_to_process)} non-exit traces.")
+        
+        # Initial save of state
+        save_state(b_set_to_process, original_traces_map)
+
+
+    for i in range(1, MAX_ITERATIONS + 1):
+        if not b_set_to_process:
+            logging.info("B set is empty. Process finished successfully.")
+            break
+
+        logging.info(f"\n--- Iteration {i}/{MAX_ITERATIONS} ---")
+        logging.info(f"Processing {len(b_set_to_process)} traces in B set.")
+
+        # Prepare input for swift CLI
+        iteration_dir = os.path.join(TMP_DIR, f'iter_{i}')
+        os.makedirs(iteration_dir, exist_ok=True)
+        iteration_input_path = os.path.join(iteration_dir, 'sample_input.jsonl')
+        swift_input_data = []
+        for trace in b_set_to_process:
+            # The swift tool is expected to take the full trace,
+            # use messages[:-1] as prompt, and messages[-1] as the ground truth for distillation.
+            swift_input_data.append({
+                "messages": trace['messages']
+            })
+        write_jsonl(iteration_input_path, swift_input_data)
+        
+        # Run swift CLI
+        # Per swift's requirement, provide a filename prefix without a directory.
+        swift_output_filename = 'sample_output.jsonl'
+        iteration_output_path = os.path.join(iteration_dir, swift_output_filename)
+
+        command = SWIFT_COMMAND_TEMPLATE.format(
+            input_file=iteration_input_path,
+            output_dir=iteration_dir,
+            output_file=swift_output_filename
+        )
+        logging.info(f"Executing Swift CLI command...")
+        
+        try:
+            # Ensure OPENAI_API_KEY is available to the subprocess
+            env = os.environ.copy()
+            if "OPENAI_API_KEY" not in env:
+                logging.warning("OPENAI_API_KEY not found in environment. The script might fail.")
+                
+            subprocess.run(command, shell=True, check=True, capture_output=True, text=True, cwd=CWD)
+            logging.info(f"Swift CLI finished. Output at {iteration_output_path}")
+        except subprocess.CalledProcessError as e:
+            logging.error(f"Swift CLI failed with exit code {e.returncode}")
+            logging.error(f"STDOUT: {e.stdout}")
+            logging.error(f"STDERR: {e.stderr}")
+            # Decide if we should stop or continue. For now, stop.
+            break
+
+        if not os.path.exists(iteration_output_path):
+            logging.warning(f"Swift output file not found at {iteration_output_path}. Assuming no traces were successfully sampled. Ending loop.")
+            break
+
+        # Process swift output and prepare for next iteration
+        b_next_iteration = []
+        extended_traces_for_rl = []
+        
+        # The output from swift contains the generated assistant message
+        generated_traces = list(read_jsonl(iteration_output_path))
+        logging.info(f"Swift generated {len(generated_traces)} successful samples.")
+
+        successful_task_ids = {get_task_id(t) for t in generated_traces}
+        successful_task_ids.discard(None)
+
+        for generated_trace in generated_traces:
+            task_id = get_task_id(generated_trace)
+            if not task_id or task_id not in original_traces_map:
+                continue
+
+            generated_messages = generated_trace['messages']
+            original_full_trace_messages = original_traces_map[task_id]
+            
+            # Extend the generated trace with the next user-assistant pair from the original trace
+            current_len = len(generated_messages)
+            if current_len + 2 <= len(original_full_trace_messages):
+                next_user_msg = original_full_trace_messages[current_len]
+                next_assistant_gt_msg = original_full_trace_messages[current_len + 1]
+
+                extended_messages = generated_messages + [next_user_msg, next_assistant_gt_msg]
+                extended_trace = {"messages": extended_messages}
+                
+                extended_traces_for_rl.append(extended_trace)
+                
+                if not is_exit_action(extended_trace):
+                    b_next_iteration.append(extended_trace)
+
+        if extended_traces_for_rl:
+            logging.info(f"Adding {len(extended_traces_for_rl)} extended traces to {FINAL_OUTPUT_PATH}")
+            write_jsonl(FINAL_OUTPUT_PATH, extended_traces_for_rl, mode='a')
+        
+        # Add back rejected tasks to be retried in the next iteration
+        rejected_count = 0
+        for original_b_trace in b_set_to_process:
+            task_id = get_task_id(original_b_trace)
+            if task_id and task_id not in successful_task_ids:
+                b_next_iteration.append(original_b_trace)
+                rejected_count += 1
+        
+        if rejected_count > 0:
+            logging.info(f"Added {rejected_count} rejected traces to the queue for retry.")
+
+        b_set_to_process = b_next_iteration
+        save_state(b_set_to_process, original_traces_map)
+
+    else: # This else belongs to the for loop, executes if loop finishes without break
+        if b_set_to_process:
+            logging.warning(f"Reached max iterations ({MAX_ITERATIONS}) but B set is not empty.")
+            logging.warning(f"{len(b_set_to_process)} traces remain.")
+
+    # Cleanup
+    if os.path.exists(PERSISTENT_STATE_FILE):
+        os.remove(PERSISTENT_STATE_FILE)
+        logging.info(f"Process finished. Removed persistent state file.")
+    
+    # Optional: You may want to clean up the tmp directory
+    # shutil.rmtree(TMP_DIR)
+    logging.info(f"Temporary files are stored in {TMP_DIR}")
+
+
+if __name__ == '__main__':
+    main()

sample/sample_test_web.sh

@@ -7,10 +7,11 @@ swift sample \
     --model $MODEL \
     --stream true \
     --orm_model external_web_acc \
-    --dataset combine_output_file_4.jsonl \
+    --dataset sample_input_step2.jsonl \
     --num_return_sequences 1 \
     --temperature 0.6 \
     --top_p 0.95 \
     --external_plugins plugin.py \
     --system system_prompt.txt \
+    --output_file sample_output_step2.jsonl \
     --engine_kwargs '{"base_url":"https://dashscope.aliyuncs.com/compatible-mode/v1"}'

sample/system_prompt.txt

@@ -18,6 +18,24 @@ def do(action, argument, element):
                 :param element: optional. Only for "Click", "Right Click", "Type", "Search", "Select Dropdown Option", and "Hover". Should be specific element id in the html.
         Returns:
                 None. The webpage will be updated after executing the action.
+            
+        IMPORTANT Notes: 
+        **1. Task Classification:**
+        - **Execution Task:** The instruction asks to perform an action, like "delete an item", "fill out a form", "navigate to a page".
+        - **Query Task:** The instruction asks to find information, like "how many items are there?", "what is the price?", "find all products".
+
+        **2. Answer Rules:**
+
+        **If the task is 'Execution':**
+        - If the task was completed successfully, the final answer should be **DONE**.
+        - If the task failed or could not be completed, the final answer should be **INFEASIBLE**.
+
+        **If the task is 'Query':**
+        - **Not Found:** If the answer is "N/A" or indicates the information could not be found, the final answer should be **N/A**.
+        - **Single Answer:** If the result is a single piece of information (e.g., a number, a name, a date), the final answer should be the most concise answer. For example, if the question is "How many products?" and the answer is "There are 5 products", the final answer should be just "5".
+        - **Multiple Answers (List):** If the result is a list of items, the final answer should be a single string with items separated by a comma. For example: "item1, item2, item3".
+        - **Multiple Answers (Key-Value):** If the result is a set of key-value pairs, the final answer should be a JSON string. For example: `{"k1": "v1", "k2": "v2"}`.
+
         """
 
 def exit(message):
@@ -45,7 +63,8 @@ do(action="Select Dropdown Option", argument="Month", element="20")
 - # Element: the 'From' date picker input field, middle center
 do(action="Type", argument="01/01/2023", element="22")
 - do(action="Scroll Down")
-- exit(message="The top-3 best-selling products in January 2023 are: 1")
+- # Note: The top-3 best-selling products in January 2023 are: 1
+exit(message="1")
 - # Element: The search bar
 do(action="Search", argument="international airport near Carnegie Mellon University within a driving distance of 50 km", element="13")
 - # Note: Pittsburgh International Airport, Southern Beltway, Findlay Township, Allegheny County, 15231, United States
@@ -65,7 +84,7 @@ Key guidelines you MUST follow:
 
 
 Your reply should strictly follow the format:
-Thought: Your reasoning trace. A good practice is to summarize information on the current web page that are relevant to the task goal, then generate a high-level plan that contains the sequence of actions you probably need to take
+Thought: Your reasoning trace. A good practice is to summarize information on the current web page that are relevant to the task goal, then generate a high-level plan that contains the sequence of actions you probably need to take. Also, use this section to record **important information** that may be useful later. For example, at each step, you might only gather a **fragment** of the overall task. Keeping track of these pieces can help you synthesize them into a complete conclusion when enough context is available.
 Action: Based on this reasoning, identify the single most optimal action. You should output it in the format specified above (under "STRICTLY follow the format")
 
 After each action, you'll receive a new observation. Proceed until task completion. Website Note "- Always save progress through appropriate buttons (Save, Submit, Post, etc.)