From 30fdd99edd74c77e9e0381795ce82c8884e14c05 Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:22:26 +0800 Subject: [PATCH 01/42] Update maindriver.sh --- flow-Agent/maindriver.sh | 28 +++++++++++++++++++++------- 1 file changed, 21 insertions(+), 7 deletions(-) diff --git a/flow-Agent/maindriver.sh b/flow-Agent/maindriver.sh index 731f332..9941e9b 100644 --- a/flow-Agent/maindriver.sh +++ b/flow-Agent/maindriver.sh @@ -1,11 +1,11 @@ #!/bin/bash # Default values -TOTAL_ITERS=6 -PARALLEL_RUNS=50 +TOTAL_ITERS=20 +PARALLEL_RUNS=4 TIMEOUT="45m" -TOTAL_CPUS=110 -TOTAL_RAM=220 +TOTAL_CPUS=8 +TOTAL_RAM=16 ECP_WEIGHT=0.5 WL_WEIGHT=0.5 ECP_WEIGHT_SURROGATE=0.5 @@ -82,6 +82,10 @@ if [[ "$objective" != "ECP" && "$objective" != "DWL" && "$objective" != "COMBO" fi # Validate weights sum to 1 +export PLATFORM=$platform +export DESIGN=$design +export OBJECTIVE=$objective + if [[ "$objective" == "COMBO" ]]; then # Ensure jq is installed if ! command -v jq &> /dev/null; then @@ -197,7 +201,8 @@ create_backup() { mkdir -p "$backup_dir" # Move config and constraint files - mv designs/${platform}/${design}/config_*.mk "$backup_dir"/ 2>/dev/null + # mv designs/${platform}/${design}/config_*.mk "$backup_dir"/ 2>/dev/null + cp designs/${platform}/${design}/config_*.mk "$backup_dir"/ 2>/dev/null mv designs/${platform}/${design}/constraint_*.sdc "$backup_dir"/ 2>/dev/null if [[ "$platform" == "asap7" && "$design" == "jpeg" ]]; then mv designs/${platform}/${design}/jpeg_encoder15_7nm_*.sdc "$backup_dir"/ 2>/dev/null @@ -222,7 +227,10 @@ for i in $(seq 1 $TOTAL_ITERS); do echo "Starting iteration $i of $TOTAL_ITERS" # Run sequential phase + # echo '"$platform" "$design" "$PARALLEL_RUNS" "$i"' + echo "${platform}, ${design}, ${PARALLEL_RUNS}, ${i}" ./run_sequential.sh "$platform" "$design" "$PARALLEL_RUNS" "$i" + echo "./run_sequential.sh \"$platform\" \"$design\" \"$PARALLEL_RUNS\" \"$i\"" # Run parallel phase with timeout timeout "$TIMEOUT" ./run_parallel.sh "$platform" "$design" "$PARALLEL_RUNS" || true @@ -235,9 +243,15 @@ for i in $(seq 1 $TOTAL_ITERS); do # Generate constraints for next iteration (skip for last iteration) if [ "$i" -lt "$TOTAL_ITERS" ]; then + for objective in "$objective"; do + echo "Running optimization for $objective" + python3 stage_optimize.py "$platform" "$design" "$objective" --max-react-steps 3 + cp -r results/ results_${platform}_${design}_${objective}/ + done echo "Running optimization for next iteration..." - python3 optimize.py "$platform" "$design" "$objective" "$PARALLEL_RUNS" + python3 optimize.py "$platform" "$design" "$objective" "$PARALLEL_RUNS" + echo "python3 optimize.py \"$platform\" \"$design\" \"$PARALLEL_RUNS\" \"$i\"" fi done -echo "All iterations complete" \ No newline at end of file +echo "All iterations complete" From ce774c919eabc7553271cec57b56bae523ddd9cf Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:28:49 +0800 Subject: [PATCH 02/42] Update optimize.py --- flow-Agent/optimize.py | 1885 +++++++++++++++++++++++++++++++++++----- 1 file changed, 1662 insertions(+), 223 deletions(-) diff --git a/flow-Agent/optimize.py b/flow-Agent/optimize.py index f8c4045..fecf05f 100644 --- a/flow-Agent/optimize.py +++ b/flow-Agent/optimize.py @@ -1,5 +1,4 @@ #!/usr/bin/env python3 - import json import os import sys @@ -9,11 +8,27 @@ import anthropic import csv import random - +from rag.util import answerWithRAG +from rag.index import load_embeddings_and_docs, build_and_save_embeddings +from sentence_transformers import SentenceTransformer +import torch +from pathlib import Path +from openai import OpenAI from inspectfuncs import * from modelfuncs import * from agglomfuncs import * +print("Python executable:", sys.executable) +print("sys.path:", sys.path[:3]) +print("Current working dir:", os.getcwd()) + +for pkg in ["anthropic", "sentence_transformers", "torch", "openai"]: + try: + __import__(pkg) + print(f"Imported {pkg}") + except ImportError as e: + print(f"Failed to import {pkg}: {e}") + def process_log_file(log_path: str) -> Dict[str, Any]: """Process a single log file to extract relevant metrics""" run_data = { @@ -25,6 +40,7 @@ def process_log_file(log_path: str) -> Dict[str, Any]: with open(log_path, 'r') as f: content = f.read() + print(f"File size: {len(content)} characters") # Extract timing information timing_metrics = extract_timing_metrics(content) @@ -37,8 +53,13 @@ def process_log_file(log_path: str) -> Dict[str, Any]: # Extract any errors errors = extract_errors(content) run_data['errors'].extend(errors) - - # Determine success based on completion markers and errors + # === Inject a simulated error for testing RAG debugging === + # if "run3" in log_path: # You can change it to any run，eg. run1 or run2 + # fake_error = "[ERROR] TEST_SIM: Simulated routing congestion failure" + # print(f"[DEBUG] Injected simulated error in {log_path}: {fake_error}") + # run_data['errors'].append(fake_error) + # run_data['success'] = False + run_data['success'] = is_run_successful(content, errors) return run_data @@ -53,17 +74,20 @@ def extract_timing_metrics(log_content: str) -> Dict[str, float]: metrics['worst_slack'] = float(slack_match.group(1)) # Extract CTS worst slack - cts_slack_match = re.search(r'(?:CTS|Clock Tree) (?:worst slack|WNS):\s*([-\d.]+)', log_content, re.IGNORECASE) + # cts_slack_match = re.search(r'(?:CTS|Clock Tree) (?:worst slack|WNS):\s*([-\d.]+)', log_content, re.IGNORECASE) + cts_slack_match = re.search(r'Timing-driven:\s*(?:worst slack|WNS)\s+([-\d.eE]+)', log_content, re.IGNORECASE) if cts_slack_match: metrics['cts_ws'] = float(cts_slack_match.group(1)) # Extract clock period - period_match = re.search(r'[Cc]lock period:\s*([\d.]+)', log_content) + # period_match = re.search(r'[Cc]lock period:\s*([\d.]+)', log_content) + period_match = re.search(r'clock period to\s*([\d.]+)', log_content) if period_match: metrics['clock_period'] = float(period_match.group(1)) # Extract TNS - tns_match = re.search(r'(?:Total negative slack|TNS):\s*([-\d.]+)', log_content, re.IGNORECASE) + # tns_match = re.search(r'(?:Total negative slack|TNS):\s*([-\d.]+)', log_content, re.IGNORECASE) + tns_match = re.search(r'"finish__timing__setup__tns"\s*:\s*([-\d.eE]+)', log_content) if tns_match: metrics['tns'] = float(tns_match.group(1)) @@ -79,7 +103,8 @@ def extract_wirelength_metrics(log_content: str) -> Dict[str, float]: metrics['total_wirelength'] = float(wl_match.group(1)) # Extract estimated wirelength after CTS - cts_wl_match = re.search(r'Estimated wirelength: ([\d.]+)', log_content) + # cts_wl_match = re.search(r'Estimated wirelength: ([\d.]+)', log_content) + cts_wl_match = re.search(r'"?cts__route__wirelength__estimated"?\s*[:=]\s*([-\d.eE]+)', log_content, re.IGNORECASE) if cts_wl_match: metrics['cts_wirelength'] = float(cts_wl_match.group(1)) @@ -103,19 +128,200 @@ def extract_errors(log_content: str) -> List[str]: return errors -def is_run_successful(log_content: str, errors: List[str]) -> bool: +def is_run_successful(log_content: str, errors: List[str], filename: str = "") -> bool: """Determine if a run was successful based on log content and errors""" if errors: + # If any real error lines were found, this file is a failure indicator return False # Look for completion markers completion_markers = [ 'Flow complete', 'Finished successfully' + 'Writing out GDS/OAS', + '6_report' ] return any(marker in log_content for marker in completion_markers) + +class ReActFramework: + """ReAct framework implementation""" + + def __init__(self, client, model_name="DeepSeek-V3"): + self.client = client + self.model_name = model_name + self.conversation_history = [] + + def add_to_history(self, role: str, content: str): + """add conversation history""" + self.conversation_history.append({"role": role, "content": content}) + + def clear_history(self): + """clear conversation history""" + self.conversation_history = [] + + def extract_thought_action(self, response: str) -> Tuple[str, str, str]: + """ + Extract Thought, Action, and Action Input from LLM responses + Format: Thought:... Action:... Action Input: ... + """ + thought = "" + action = "" + action_input = "" + + # Extract Thought + thought_match = re.search(r'Thought:\s*(.*?)(?=\nAction:|$)', response, re.DOTALL) + if thought_match: + thought = thought_match.group(1).strip() + + # Extract Action + action_match = re.search(r'Action:\s*(\w+)', response) + if action_match: + action = action_match.group(1).strip() + + # Extract Action Input + action_input_match = re.search(r'Action Input:\s*(.*?)(?=\nObservation:|$)', response, re.DOTALL) + if action_input_match: + action_input = action_input_match.group(1).strip() + # Try to parse JSON + try: + if action_input.startswith('{') or action_input.startswith('['): + action_input = json.loads(action_input) + except: + pass # Maintain the string format + + if "Final Answer:" in response and ("Action:" in response or "Observation:" in response): + + response = response.split("Final Answer:")[0] + print("Removed premature Final Answer from response") + + return thought, action, action_input + + def execute_action(self, action: str, action_input: Any, available_tools: Dict) -> str: + """Execute tool call and return observation results""" + if action in available_tools: + try: + result = available_tools[action](action_input) + return f"Action executed successfully. Result: {result}" + except Exception as e: + return f"Action execution failed: {str(e)}" + else: + return f"Unknown action: {action}. Available actions: {list(available_tools.keys())}" + + def run_react_cycle(self, + initial_prompt: str, + available_tools: Dict, + max_steps: int = 5, + temperature: float = 0.1) -> Dict[str, Any]: + """ + Run ReAct loop + + Args: + initial_prompt: Initial prompt + available_tools: Available tool function dictionary + max_steps: Maximum reasoning steps + temperature: temperature parameter + + Returns: + a dictionary containing the final result and the reasoning history + """ + self.clear_history() + self.add_to_history("user", initial_prompt) + + history = [] + final_answer = None + completed_steps = 0 + + for step in range(max_steps): + print(f"\n=== ReAct Step {step + 1}/{max_steps} ===") + completed_steps = step + 1 + + # Call LLM to obtain response + try: + response = self.client.chat.completions.create( + model=self.model_name, + messages=self.conversation_history, + temperature=temperature, + max_tokens=1024 + ) + + llm_response = response.choices[0].message.content + print(f"LLM Response: {llm_response}") + except Exception as e: + print(f"Error calling LLM: {e}") + llm_response = f"Error in LLM call: {e}" + + # Extract Thought, Action, Action Input + thought, action, action_input = self.extract_thought_action(llm_response) + + step_data = { + "step": step + 1, + "thought": thought, + "action": action, + "action_input": action_input, + "llm_response": llm_response + } + + # Check if it is the final answer + final_answer_detected = False + if "Final Answer:" in llm_response: + final_answer_match = re.search(r'Final Answer:\s*(.*?)$', llm_response, re.DOTALL) + if final_answer_match: + final_answer = final_answer_match.group(1).strip() + step_data["final_answer"] = final_answer + final_answer_detected = True + print(f"Final answer detected at step {step + 1}") + + observation = "" + # Execute actions and obtain observation results + if action and not final_answer_detected: + observation = self.execute_action(action, action_input, available_tools) + step_data["observation"] = observation + + # Update conversation history + self.add_to_history("assistant", llm_response) + self.add_to_history("user", f"Observation: {observation}") + + print(f"Thought: {thought}") + print(f"Action: {action}") + print(f"Action Input: {action_input}") + print(f"Observation: {observation}") + else: + if not final_answer_detected: + # If there is no clear action, it may be during the reasoning process + self.add_to_history("assistant", llm_response) + step_data["observation"] = "No action taken - continuing reasoning" + observation = "No action taken" + else: + # If it is the final answer, no further action is required + step_data["observation"] = "Final answer provided - cycle complete" + observation = "Final answer provided" + + history.append(step_data) + + if final_answer_detected: + print(f" ReAct cycle completed at step {step + 1} with final answer") + break + + # Check if it should end early + if step >= max_steps - 1: + final_answer = f"Reached maximum steps ({max_steps}) without final answer" + print(f" Reached maximum steps without final answer") + break + + if final_answer is None: + final_answer = "No final answer produced" + + return { + "final_answer": final_answer, + "reasoning_history": history, + "success": final_answer is not None and "Reached maximum steps" not in final_answer and "No final answer" not in final_answer, + "completed_steps": completed_steps, + "max_steps": max_steps + } + + class OptimizationWorkflow: def __init__(self, platform: str, design: str, objective: str): self.platform = platform @@ -196,6 +402,974 @@ def __init__(self, platform: str, design: str, objective: str): # Load initial parameters and SDC context self.initial_params = self._load_initial_params() self.sdc_context = self._load_sdc_context() + + emb_np, docs, docsDict = load_embeddings_and_docs() + self.rag_embeddings = torch.tensor(emb_np).cpu() + self.rag_docs = docs + self.rag_docsDict = docsDict + print("[INFO] Loading embedding model...") + model_path = Path(__file__).parent / "models" / "mxbai-embed-large-v1" + model_path = model_path.resolve() + self.rag_model = SentenceTransformer(str(model_path)) + + self.react_framework = ReActFramework( + client=OpenAI( + base_url="https://ai.gitee.com/v1", + api_key=" ", + ), + model_name="DeepSeek-V3" + ) + + def _create_react_tools(self, stage: str, data: Dict[str, Any]) -> Dict: + """Create available utility functions for different stages""" + + base_tools = { + "analyze_data_distribution": lambda x: self._call_existing_distribution_analysis(data), + "analyze_data_structure": lambda x: self._call_existing_structure_analysis(data), + "evaluate_parameter_ranges": lambda x: self._evaluate_parameter_ranges(data), + "check_constraints": lambda x: self._check_constraints_compliance(data), + "suggest_improvements": lambda x: self._suggest_improvements(stage, data), + } + + if stage == 'inspect': + inspection_tools = { + "configure_inspection": lambda config: self._configure_inspection_with_existing(config, data), + "analyze_correlations": lambda params: self._analyze_correlations_with_existing(params, data), + "cluster_analysis": lambda config: self._cluster_analysis_with_existing(config, data), + "manifold_analysis": lambda config: self._manifold_analysis_with_existing(config, data), + "local_structure_analysis": lambda config: self._local_structure_analysis_with_existing(config, data), + } + base_tools.update(inspection_tools) + + elif stage == 'model': + modeling_tools = { + "configure_model": lambda config: self._configure_model_with_existing(config, data), + "evaluate_surrogate": lambda params: self._evaluate_surrogate_with_existing(params, data), + "select_acquisition": lambda method: self._select_acquisition_with_existing(method, data), + "create_surrogate_model": lambda config: self._create_surrogate_model_with_existing(config, data), + "evaluate_timing_model": lambda x: self._evaluate_timing_model_with_existing(data), + "evaluate_wirelength_model": lambda x: self._evaluate_wirelength_model_with_existing(data), + "get_model_recommendations": lambda x: self._get_model_recommendations_from_existing(data), + } + base_tools.update(modeling_tools) + + elif stage == 'agglomerate': + selection_tools = { + "configure_selection": lambda config: self._configure_selection_with_existing(config, data), + "generate_parameters": lambda count: self._generate_parameters_with_existing(count, data), + "validate_parameters": lambda params: self._validate_parameters_tool(params), + "latin_hypercube_sampling": lambda config: self._latin_hypercube_sampling_with_existing(config, data), + "create_quality_scores": lambda config: self._create_quality_scores_with_existing(config, data), + "select_points": lambda config: self._select_points_with_existing(config, data), + "compare_selection_methods": lambda config: self._compare_selection_methods_with_existing(config, data), + "kmeans_selection": lambda config: self._kmeans_selection_with_existing(config, data), + "hybrid_selection": lambda config: self._hybrid_selection_with_existing(config, data), + "entropy_selection": lambda config: self._entropy_selection_with_existing(config, data), + "graph_selection": lambda config: self._graph_selection_with_existing(config, data), + } + base_tools.update(selection_tools) + + return base_tools + + + def _call_existing_distribution_analysis(self, data: Dict) -> str: + """Call existing data distribution analysis functions""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + result = inspect_data_distribution(X, Y) + return self._format_analysis_result("Data Distribution Analysis", result) + else: + return "Insufficient data for distribution analysis" + + except Exception as e: + return f"Error in distribution analysis: {str(e)}" + + def _call_existing_structure_analysis(self, data: Dict) -> str: + """Call existing data structure analysis functions""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + # Use default configuration or retrieve configuration from data + config = { + "n_clusters": 5, + "correlation_threshold": 0.5, + "n_neighbors": 20, + "perplexity": 30 + } + + result = inspect_data_structure(X, Y, config) + return self._format_analysis_result("Data Structure Analysis", result) + else: + return "Insufficient data for structure analysis" + + except Exception as e: + return f"Error in structure analysis: {str(e)}" + + def _evaluate_parameter_ranges(self, data: Dict) -> str: + """Evaluation Parameter Range Tool - Implementation""" + constraints_info = "Parameter Constraints Evaluation:\n" + + # Analyze the current usage of parameters + param_usage = {} + for run in data.get('log_data', {}).get('runs', []): + if run.get('parameters'): + for param, value in run['parameters'].items(): + if param not in param_usage: + param_usage[param] = [] + param_usage[param].append(float(value)) + + for param, info in self.param_constraints.items(): + min_val, max_val = info['range'] + param_type = info['type'] + + constraints_info += f"\n- {param} ({param_type}): range [{min_val}, {max_val}]" + + if param in param_usage: + values = param_usage[param] + used_min = min(values) + used_max = max(values) + constraints_info += f"\n Currently used: [{used_min:.2f}, {used_max:.2f}]" + + # Check if the parameter space has been fully explored + range_used = (used_max - used_min) / (max_val - min_val) + if range_used < 0.5: + constraints_info += f" (Only {range_used*100:.1f}% of range explored)" + + return constraints_info + + def _check_constraints_compliance(self, data: Dict) -> str: + """Check Constraint Compliance Tool - Implementation""" + violations = [] + constraint_checks = [] + + for run in data.get('log_data', {}).get('runs', []): + if run.get('success') and run.get('parameters'): + params = run['parameters'] + + # Check the basic scope constraints + for param, value in params.items(): + if param in self.param_constraints: + constraint = self.param_constraints[param] + min_val, max_val = constraint['range'] + if value < min_val or value > max_val: + violations.append(f"{param}={value} not in [{min_val}, {max_val}]") + + # Check domain constraints + if not self._validate_domain_constraints(params): + violations.append(f"Domain constraints violated for run with params: {params}") + + if violations: + constraint_checks.append(f"Constraint violations found in {len(violations)} cases:") + constraint_checks.extend(violations[:5]) # Only display the first 5 + else: + constraint_checks.append("All parameters comply with constraints") + + # Check the effectiveness of parameter combinations + successful_count = sum(1 for run in data.get('log_data', {}).get('runs', []) + if run.get('success') and run.get('parameters')) + total_with_params = sum(1 for run in data.get('log_data', {}).get('runs', []) + if run.get('parameters')) + + if total_with_params > 0: + success_rate = successful_count / total_with_params * 100 + constraint_checks.append(f"\nParameter success rate: {success_rate:.1f}%") + + return "\n".join(constraint_checks) + + def _suggest_improvements(self, stage: str, data: Dict) -> str: + """Provide improvement suggestions based on stages - implementation""" + suggestions = [] + + if stage == 'inspect': + successful_runs = data.get('log_data', {}).get('summary', {}).get('successful_runs', 0) + total_runs = data.get('log_data', {}).get('summary', {}).get('total_runs', 0) + + suggestions.append(f"Inspection Suggestions for {successful_runs}/{total_runs} successful runs:") + + if successful_runs < total_runs * 0.3: + suggestions.append("- Focus on identifying why runs are failing") + suggestions.append("- Check for common parameter ranges in failed runs") + else: + suggestions.append("- Analyze correlations between parameters and objectives") + suggestions.append("- Identify optimal parameter ranges from successful runs") + + elif stage == 'model': + suggestions.append("Modeling Suggestions:") + suggestions.append("- Use surrogate models for early prediction of results") + suggestions.append("- Balance exploration (trying new regions) and exploitation (refining good regions)") + + # Suggest modeling methods based on data volume + successful_runs = data.get('log_data', {}).get('summary', {}).get('successful_runs', 0) + if successful_runs < 10: + suggestions.append("- With limited data, use simpler models and focus on exploration") + else: + suggestions.append("- With sufficient data, use more complex models and balance exploration/exploitation") + + elif stage == 'agglomerate': + suggestions.append("Parameter Generation Suggestions:") + suggestions.append("- Generate diverse parameter sets to explore different regions") + suggestions.append("- Focus on promising parameter ranges identified in previous stages") + suggestions.append("- Ensure all generated parameters satisfy domain constraints") + + # Suggest strategies based on goals + if self.objective == 'ECP': + suggestions.append("- For ECP, prioritize timing-critical parameters like clk_period and cell padding") + elif self.objective == 'DWL': + suggestions.append("- For DWL, focus on placement and routing parameters") + + return "\n".join(suggestions) + + def _extract_XY_from_data(self, data: Dict) -> Tuple[Optional[np.ndarray], Optional[np.ndarray]]: + """Extracting X and Y arrays from data - Reusing logic in analyze_stetrics""" + feature_vectors = [] + objective_values = [] + + for run in data.get('log_data', {}).get('runs', []): + if run.get('success') and 'metrics' in run: + obj_values = self._calculate_objective(run) + + if obj_values['value'] is not None or obj_values['surrogate'] is not None: + # Extract parameter values as features + params = [] + for param in self.parameter_names: + params.append(float(run.get('parameters', {}).get(param, self.initial_params.get(param, 0)))) + feature_vectors.append(params) + + # Use real values, if not available, use proxy values + objective_values.append(obj_values['value'] if obj_values['value'] is not None else obj_values['surrogate']) + + if feature_vectors and objective_values: + return np.array(feature_vectors), np.array(objective_values) + else: + return None, None + + def _format_analysis_result(self, title: str, result: Dict) -> str: + """Format the analysis result as a readable string""" + formatted = f"=== {title} ===\n" + + for key, value in result.items(): + if key == "model_recommendations": + formatted += "\n--- Model Recommendations ---\n" + for rec_key, rec_value in value.items(): + formatted += f"{rec_key}: {rec_value}\n" + elif isinstance(value, (int, float)): + formatted += f"{key}: {value:.4f}\n" + elif isinstance(value, list) and len(value) > 0 and isinstance(value[0], (int, float)): + # Format numerical list + formatted += f"{key}: [{', '.join(f'{v:.4f}' for v in value[:5])}{'...' if len(value) > 5 else ''}]\n" + else: + formatted += f"{key}: {value}\n" + + return formatted + + def _configure_inspection_with_existing(self, config: Dict, data: Dict) -> str: + """Use existing function configuration to check parameters""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + # Using configuration to run structural analysis + result = inspect_data_structure(X, Y, config) + + response = f"Inspection configured with: {config}\n" + response += "Key findings:\n" + + # Extract key findings + if "linearity_score" in result: + response += f"- Linearity: {result['linearity_score']:.3f}\n" + if "is_nonlinear" in result: + response += f"- Nonlinear: {result['is_nonlinear']}\n" + if "needs_local_models" in result: + response += f"- Needs local models: {result['needs_local_models']}\n" + if "cluster_sizes" in result: + response += f"- Cluster sizes: {result['cluster_sizes']}\n" + + return response + else: + return "No data available for inspection configuration" + + except Exception as e: + return f"Error in inspection configuration: {str(e)}" + + def _analyze_correlations_with_existing(self, params: Dict, data: Dict) -> str: + """Analyze correlation using existing functions""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + # Perform structural analysis to obtain relevant information + config = {"correlation_threshold": params.get('threshold', 0.5)} + result = inspect_data_structure(X, Y, config) + + response = "Feature Correlations Analysis:\n" + + if "feature_importance" in result: + response += "Feature importance (correlation with objective):\n" + for i, importance in enumerate(result["feature_importance"]): + response += f"- {self.parameter_names[i]}: {importance:.3f}\n" + + if "has_correlated_features" in result: + response += f"Has highly correlated features: {result['has_correlated_features']}\n" + if "high_correlation_pairs" in result: + response += f"High correlation pairs: {result['high_correlation_pairs']}\n" + + return response + else: + return "No data available for correlation analysis" + + except Exception as e: + return f"Error in correlation analysis: {str(e)}" + + def _cluster_analysis_with_existing(self, config: Dict, data: Dict) -> str: + """Cluster analysis using existing functions""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + # Perform structural analysis to obtain clustering information + result = inspect_data_structure(X, Y, config) + + response = "Cluster Analysis:\n" + + if "cluster_sizes" in result: + response += f"Cluster sizes: {result['cluster_sizes']}\n" + if "cluster_balance" in result: + response += f"Cluster balance: {result['cluster_balance']:.3f}\n" + if "cluster_y_means" in result: + response += "Cluster objective means:\n" + for i, mean in enumerate(result["cluster_y_means"]): + response += f"- Cluster {i}: {mean:.4f}\n" + if "needs_local_models" in result: + response += f"Recommend local models: {result['needs_local_models']}\n" + + return response + else: + return "No data available for cluster analysis" + + except Exception as e: + return f"Error in cluster analysis: {str(e)}" + + def _manifold_analysis_with_existing(self, config: Dict, data: Dict) -> str: + """Perform manifold analysis using existing functions""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None: + result = analyze_manifold_structure(X, config) + return self._format_analysis_result("Manifold Structure Analysis", result) + else: + return "No data available for manifold analysis" + + except Exception as e: + return f"Error in manifold analysis: {str(e)}" + + def _local_structure_analysis_with_existing(self, config: Dict, data: Dict) -> str: + """Using existing functions for local structure analysis""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None: + result = analyze_local_structure(X, config) + return self._format_analysis_result("Local Structure Analysis", result) + else: + return "No data available for local structure analysis" + + except Exception as e: + return f"Error in local structure analysis: {str(e)}" + + def _get_model_recommendations_from_existing(self, data: Dict) -> str: + """Obtain model recommendations from existing analysis""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + result = inspect_data_structure(X, Y) + + if "model_recommendations" in result: + recommendations = result["model_recommendations"] + response = "Model Recommendations from Data Analysis:\n" + + for key, value in recommendations.items(): + if key == "feature_weights" and isinstance(value, list): + response += f"{key}: [" + response += ", ".join(f"{w:.3f}" for w in value[:5]) + if len(value) > 5: + response += ", ..." + response += "]\n" + else: + response += f"{key}: {value}\n" + + return response + else: + return "No model recommendations available" + else: + return "No data available for model recommendations" + + except Exception as e: + return f"Error getting model recommendations: {str(e)}" + + + def _configure_model_with_existing(self, config: Dict, data: Dict) -> str: + """Configure the model using existing functions""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + # Create a model using configuration + kernel_type = config.get('kernel_type', 'matern') + preprocessing = config.get('preprocessing', 'standard') + acquisition = config.get('acquisition', 'ei') + + # Create Preprocessor + preprocessor = create_preprocessor(preprocessing) + + # Create acquisition function + acq_function = create_acquisition_function(acquisition) + + response = f"Model configured successfully:\n" + response += f"- Kernel type: {kernel_type}\n" + response += f"- Preprocessing: {preprocessing}\n" + response += f"- Acquisition function: {acquisition}\n" + response += f"- Data shape: {X.shape}\n" + + # If the amount of data is sufficient, a model can be created for testing + if len(X) >= 2: + model = create_model(X, Y, kernel_type=kernel_type) + response += f"- Model created successfully with {len(X)} samples\n" + else: + response += f"- Insufficient data for model creation (need at least 2 samples, have {len(X)})\n" + + return response + else: + return "No data available for model configuration" + + except Exception as e: + return f"Error in model configuration: {str(e)}" + + def _evaluate_surrogate_with_existing(self, params: Dict, data: Dict) -> str: + """Evaluate the proxy model using existing functions""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + # Extract proxy values (if any) + surrogate_values = None + if 'surrogates' in data.get('metrics', {}): + surrogate_values = np.array(data['metrics']['surrogates']) + + # Use existing functions to process proxy data + if surrogate_values is not None: + X_processed, y_combined, uncertainty = handle_surrogate_data(X, Y, surrogate_values) + + response = "Surrogate Model Evaluation:\n" + response += f"- Original data points: {len(Y)}\n" + response += f"- Valid target values: {np.sum(~np.isnan(Y))}\n" + response += f"- Surrogate values used: {np.sum(np.isnan(Y))}\n" + response += f"- Combined data points: {len(y_combined)}\n" + + if len(uncertainty) > 0: + response += f"- Average surrogate uncertainty: {np.mean(uncertainty):.4f}\n" + + return response + else: + return "No surrogate data available for evaluation" + else: + return "No data available for surrogate evaluation" + + except Exception as e: + return f"Error in surrogate evaluation: {str(e)}" + + def _select_acquisition_with_existing(self, method: str, data: Dict) -> str: + """Use existing functions to select collection functions""" + try: + # Create a collection function using an existing function + acq_function = create_acquisition_function(method) + + response = f"Acquisition function selected: {method.upper()}\n" + + # Provide explanations for different collection functions + explanations = { + 'ei': "Expected Improvement - balances improvement probability and magnitude", + 'ucb': "Upper Confidence Bound - favors exploration of uncertain regions", + 'pi': "Probability of Improvement - focuses on areas likely to improve", + 'augmented_ei': "Augmented EI - combines EI with exploration bonus" + } + + response += f"Explanation: {explanations.get(method, 'No explanation available')}\n" + + # Provide recommendations based on data characteristics + X, Y = self._extract_XY_from_data(data) + if X is not None and Y is not None: + if len(Y) < 10: + response += "Recommendation: With limited data, consider using UCB for better exploration\n" + else: + response += "Recommendation: With sufficient data, EI or Augmented EI are good choices\n" + + return response + + except Exception as e: + return f"Error in acquisition function selection: {str(e)}" + + def _create_surrogate_model_with_existing(self, config: Dict, data: Dict) -> str: + """Create a proxy model using existing functions""" + try: + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + kernel_type = config.get('kernel_type', 'matern') + noise_level = config.get('noise_level', 1e-6) + + # Create a model using existing functions + model = create_model(X, Y, noise_level=noise_level, kernel_type=kernel_type) + + response = f"Surrogate Model Created:\n" + response += f"- Kernel: {kernel_type}\n" + response += f"- Data points: {len(X)}\n" + response += f"- Features: {X.shape[1]}\n" + response += f"- Kernel parameters: {model.kernel_}\n" + + # Test model prediction + if len(X) > 0: + predictions, stds = predict_with_model(model, X[:1]) # Test a point + response += f"- Test prediction successful\n" + response += f"- Prediction range: [{predictions[0]:.4f} ± {stds[0]:.4f}]\n" + + return response + else: + return "No data available for model creation" + + except Exception as e: + return f"Error in surrogate model creation: {str(e)}" + + def _evaluate_timing_model_with_existing(self, data: Dict) -> str: + """Evaluate timing models using existing functions""" + try: + # Build context + context = { + 'log_data': data.get('log_data', {}), + 'metrics': data.get('metrics', {}), + 'model_recommendations': data.get('model_recommendations', {}) + } + + # Evaluate timing models using existing functions + results = evaluate_timing_model(context) + + response = "Timing Model Evaluation:\n" + + if 'performance' in results: + for key, value in results['performance'].items(): + response += f"- {key}: {value:.4f}\n" + + if 'suggestions' in results: + response += "\nSuggestions:\n" + for suggestion in results['suggestions']: + response += f"- {suggestion}\n" + + if 'recommendations' in results: + response += "\nRecommendations:\n" + for key, value in results['recommendations'].items(): + response += f"- {key}: {value}\n" + + return response + + except Exception as e: + return f"Error in timing model evaluation: {str(e)}" + + def _evaluate_wirelength_model_with_existing(self, data: Dict) -> str: + """Evaluate the wire length model using existing functions""" + try: + # Build context + context = { + 'log_data': data.get('log_data', {}), + 'metrics': data.get('metrics', {}), + 'model_recommendations': data.get('model_recommendations', {}) + } + + # Evaluate the wire length model using existing functions + results = evaluate_wirelength_model(context) + + response = "Wirelength Model Evaluation:\n" + + if 'performance' in results: + for key, value in results['performance'].items(): + response += f"- {key}: {value:.4f}\n" + + if 'suggestions' in results: + response += "\nSuggestions:\n" + for suggestion in results['suggestions']: + response += f"- {suggestion}\n" + + if 'recommendations' in results: + response += "\nRecommendations:\n" + for key, value in results['recommendations'].items(): + response += f"- {key}: {value}\n" + + return response + + except Exception as e: + return f"Error in wirelength model evaluation: {str(e)}" + + def _generate_parameters_with_existing(self, count: int, data: Dict) -> str: + """Generate parameters using existing functions""" + try: + if count <= 0 or count > 50: + return "Error: count must be between 1 and 50" + + # Obtain parameter dimensions + n_dims = len(self.parameter_names) + + # Use existing Latin hypercube sampling + samples = latin_hypercube(count, n_dims) + + response = f"Parameter Generation using Latin Hypercube:\n" + response += f"- Samples generated: {count}\n" + response += f"- Parameter dimensions: {n_dims}\n" + response += f"- Sampling method: Latin Hypercube\n" + + # Display parameter range information + response += "\nParameter Ranges:\n" + for i, param in enumerate(self.parameter_names): + constraint = self.param_constraints[param] + min_val, max_val = constraint['range'] + response += f"- {param}: [{min_val}, {max_val}] ({constraint['type']})\n" + + return response + + except Exception as e: + return f"Error in parameter generation: {str(e)}" + + def _latin_hypercube_sampling_with_existing(self, config: Dict, data: Dict) -> str: + """Using existing functions for Latin hypercube sampling""" + try: + n_points = config.get('n_points', 10) + n_dims = len(self.parameter_names) + + # Use the existing Latin hypercube sampling function + samples = latin_hypercube(n_points, n_dims) + + response = f"Latin Hypercube Sampling:\n" + response += f"- Points: {n_points}\n" + response += f"- Dimensions: {n_dims}\n" + response += f"- Sample shape: {samples.shape}\n" + + # Display sampling statistics + response += f"- Sample range: [{samples.min():.3f}, {samples.max():.3f}]\n" + response += f"- Sample mean: {samples.mean():.3f}\n" + response += f"- Sample std: {samples.std():.3f}\n" + + return response + + except Exception as e: + return f"Error in Latin hypercube sampling: {str(e)}" + + def _configure_selection_with_existing(self, config: Dict, data: Dict) -> str: + """Configure selection strategy using existing functions""" + try: + method = config.get('method', 'hybrid') + quality_weight = config.get('quality_weight', 0.7) + uncertainty_bonus = config.get('uncertainty_bonus', 0.2) + n_points = config.get('n_points', 10) + + response = f"Selection Strategy Configured:\n" + response += f"- Method: {method}\n" + response += f"- Quality weight: {quality_weight}\n" + response += f"- Uncertainty bonus: {uncertainty_bonus}\n" + response += f"- Points to select: {n_points}\n" + + # Provide explanations for different methods + method_descriptions = { + "kmeans": "K-means clustering - selects best point from each cluster", + "hybrid": "Hybrid approach - balances quality and diversity", + "entropy": "Entropy-based - maximizes information diversity", + "graph": "Graph-based - uses network centrality measures" + } + + response += f"Method description: {method_descriptions.get(method, 'No description')}\n" + + return response + + except Exception as e: + return f"Error in selection configuration: {str(e)}" + + + def _create_quality_scores_with_existing(self, config: Dict, data: Dict) -> str: + """Create a quality score using an existing function""" + try: + # Extract necessary information from data + X, Y = self._extract_XY_from_data(data) + + if X is not None and Y is not None: + # Simulation model predictions and uncertainties (in practical use, these should come from real models) + model_predictions = Y # Using real values as a proxy for prediction + model_uncertainties = np.ones_like(Y) * 0.1 # Simulate uncertainty + + # Create a quality score using an existing function + quality_scores = create_quality_scores(X, Y, model_predictions, model_uncertainties) + + response = "Quality Scores Created:\n" + response += f"- Data points: {len(X)}\n" + response += f"- Quality score range: [{quality_scores.min():.4f}, {quality_scores.max():.4f}]\n" + response += f"- Quality score mean: {quality_scores.mean():.4f}\n" + response += f"- Quality score std: {quality_scores.std():.4f}\n" + + response += f"- First 5 quality scores: {quality_scores[:5].tolist()}\n" + + if 'selection_data' not in data: + data['selection_data'] = {} + data['selection_data']['quality_scores'] = quality_scores + data['selection_data']['X'] = X + data['selection_data']['Y'] = Y + + return response + else: + return "No data available for quality score creation" + + except Exception as e: + return f"Error in quality score creation: {str(e)}" + + def _select_points_with_existing(self, config: Dict, data: Dict) -> str: + """_select_points_with_existing""" + try: + selection_data = data.get('selection_data', {}) + quality_scores = selection_data.get('quality_scores') + X = selection_data.get('X') + + if X is not None and quality_scores is not None: + method = config.get('method', 'hybrid') + n_points = config.get('n_points', 10) + quality_weight = config.get('quality_weight', 0.7) + + selection_config = { + "quality_weight": quality_weight, + "uncertainty_bonus": config.get('uncertainty_bonus', 0.2) + } + + selected_indices = select_points( + X, quality_scores, + method=method, + n_points=n_points, + config=selection_config + ) + + response = f"Points Selected using {method.upper()} method:\n" + response += f"- Selected {len(selected_indices)} points\n" + response += f"- Selected indices: {selected_indices.tolist()}\n" + + selected_qualities = quality_scores[selected_indices] + response += f"- Selected quality scores: {selected_qualities.tolist()}\n" + response += f"- Average quality of selected: {selected_qualities.mean():.4f}\n" + + # store selection data + data['selection_data']['selected_indices'] = selected_indices + + return response + else: + return "No quality scores available. Please run 'create_quality_scores' first." + + except Exception as e: + return f"Error in point selection: {str(e)}" + + def _compare_selection_methods_with_existing(self, config: Dict, data: Dict) -> str: + """compare selection methods with existing(""" + try: + selection_data = data.get('selection_data', {}) + quality_scores = selection_data.get('quality_scores') + X = selection_data.get('X') + + if X is not None and quality_scores is not None: + n_points = config.get('n_points', 5) + methods = ['kmeans', 'hybrid', 'entropy', 'graph'] + + response = "Selection Method Comparison:\n" + response += f"- Comparing {len(methods)} methods\n" + response += f"- Points to select: {n_points}\n\n" + + for method in methods: + try: + selected_indices = select_points( + X, quality_scores, + method=method, + n_points=n_points + ) + + selected_qualities = quality_scores[selected_indices] + + response += f"**{method.upper()}**:\n" + response += f" - Selected indices: {selected_indices.tolist()}\n" + response += f" - Avg quality: {selected_qualities.mean():.4f}\n" + response += f" - Quality range: [{selected_qualities.min():.4f}, {selected_qualities.max():.4f}]\n" + + except Exception as e: + response += f"**{method.upper()}**: Error - {str(e)}\n" + + return response + else: + return "No quality scores available. Please run 'create_quality_scores' first." + + except Exception as e: + return f"Error in method comparison: {str(e)}" + + def _kmeans_selection_with_existing(self, config: Dict, data: Dict) -> str: + """using K-means selection method""" + try: + selection_data = data.get('selection_data', {}) + quality_scores = selection_data.get('quality_scores') + X = selection_data.get('X') + + if X is not None and quality_scores is not None: + n_points = config.get('n_points', 10) + + # using K-means selecting function + selected_indices = kmeans_select(X, quality_scores, n_points) + + response = "K-means Selection Results:\n" + response += f"- Selected {len(selected_indices)} points\n" + response += f"- Selected indices: {selected_indices.tolist()}\n" + + selected_qualities = quality_scores[selected_indices] + response += f"- Average quality: {selected_qualities.mean():.4f}\n" + response += f"- Quality diversity: {selected_qualities.std():.4f}\n" + + # store results + data['selection_data']['selected_indices'] = selected_indices + data['selection_data']['method_used'] = 'kmeans' + + return response + else: + return "No quality scores available. Please run 'create_quality_scores' first." + + except Exception as e: + return f"Error in K-means selection: {str(e)}" + + def _hybrid_selection_with_existing(self, config: Dict, data: Dict) -> str: + """using existing hybrid selection method""" + try: + selection_data = data.get('selection_data', {}) + quality_scores = selection_data.get('quality_scores') + X = selection_data.get('X') + + if X is not None and quality_scores is not None: + n_points = config.get('n_points', 10) + quality_weight = config.get('quality_weight', 0.7) + + distance_matrix = cdist(X, X) + + # using hybrid_select function + selected_indices = hybrid_select( + X, quality_scores, distance_matrix, + n_points, quality_weight + ) + + response = "Hybrid Selection Results:\n" + response += f"- Selected {len(selected_indices)} points\n" + response += f"- Quality weight: {quality_weight}\n" + response += f"- Selected indices: {selected_indices.tolist()}\n" + + selected_qualities = quality_scores[selected_indices] + response += f"- Average quality: {selected_qualities.mean():.4f}\n" + + selected_points = X[selected_indices] + min_distances = np.min(cdist(selected_points, selected_points) + np.eye(len(selected_points)) * 1e6, axis=1) + response += f"- Minimum inter-point distance: {min_distances.mean():.4f}\n" + + # store results + data['selection_data']['selected_indices'] = selected_indices + data['selection_data']['method_used'] = 'hybrid' + + return response + else: + return "No quality scores available. Please run 'create_quality_scores' first." + + except Exception as e: + return f"Error in hybrid selection: {str(e)}" + + def _entropy_selection_with_existing(self, config: Dict, data: Dict) -> str: + """using existing entropy selecting methods""" + try: + selection_data = data.get('selection_data', {}) + quality_scores = selection_data.get('quality_scores') + X = selection_data.get('X') + + if X is not None and quality_scores is not None: + n_points = config.get('n_points', 10) + + # using entropy selecting function + selected_indices = entropy_select(X, quality_scores, n_points) + + response = "Entropy-based Selection Results:\n" + response += f"- Selected {len(selected_indices)} points\n" + response += f"- Selected indices: {selected_indices.tolist()}\n" + + selected_qualities = quality_scores[selected_indices] + response += f"- Average quality: {selected_qualities.mean():.4f}\n" + + # store results + data['selection_data']['selected_indices'] = selected_indices + data['selection_data']['method_used'] = 'entropy' + + return response + else: + return "No quality scores available. Please run 'create_quality_scores' first." + + except Exception as e: + return f"Error in entropy selection: {str(e)}" + + def _graph_selection_with_existing(self, config: Dict, data: Dict) -> str: + """using existing graph selection method""" + try: + selection_data = data.get('selection_data', {}) + quality_scores = selection_data.get('quality_scores') + X = selection_data.get('X') + + if X is not None and quality_scores is not None: + n_points = config.get('n_points', 10) + + # using graph selecting function + selected_indices = graph_select(X, quality_scores, n_points) + + response = "Graph-based Selection Results:\n" + response += f"- Selected {len(selected_indices)} points\n" + response += f"- Selected indices: {selected_indices.tolist()}\n" + + selected_qualities = quality_scores[selected_indices] + response += f"- Average quality: {selected_qualities.mean():.4f}\n" + + # store results + data['selection_data']['selected_indices'] = selected_indices + data['selection_data']['method_used'] = 'graph' + + return response + else: + return "No quality scores available. Please run 'create_quality_scores' first." + + except Exception as e: + return f"Error in graph selection: {str(e)}" + + + def _validate_parameters_tool(self, params: Dict) -> str: + validation_results = [] + + for param_name, value in params.items(): + if param_name in self.param_constraints: + constraint = self.param_constraints[param_name] + min_val, max_val = constraint['range'] + param_type = constraint['type'] + + if value < min_val or value > max_val: + validation_results.append(f" {param_name}={value} outside range [{min_val}, {max_val}]") + else: + validation_results.append(f" {param_name}={value} within valid range") + + if self._validate_domain_constraints(params): + validation_results.append("Domain constraints satisfied") + else: + validation_results.append("Domain constraints violated") + + return "Parameter Validation:\n" + "\n".join(validation_results) + def _load_config(self) -> Dict[str, Any]: """Load the configuration from 'opt_config.json'.""" @@ -249,41 +1423,40 @@ def _load_sdc_context(self) -> Dict[str, Any]: return sdc_context + def _generate_llm_prompt(self, stage: str, data: Dict[str, Any]) -> str: - """Generate LLM prompt for different stages""" - # Include parameter constraints in the prompt constraints_text = "Parameter Constraints:\n" for param, info in self.param_constraints.items(): param_type = info['type'] param_range = info['range'] constraints_text += f"- {param} ({param_type}, range: {param_range})\n" - # Construct the prompt based on the stage - if stage == 'inspect': - prompt = ( + tool_instructions = { + 'inspect': ( f"**Stage: Inspect**\n" "In this stage, we analyze the data from previous optimization runs to identify patterns, trends, and insights.\n\n" - f"Data to analyze:\n{json.dumps(data, indent=2)}\n\n" + f"Data to analyze:\n{json.dumps(data, indent=2, default=str)}\n\n" "Please analyze the data and provide insights on:\n" "1. Key patterns in successful vs unsuccessful runs.\n" "2. Parameter ranges that appear promising.\n" "3. Any timing or wirelength trends.\n" "4. Recommendations for subsequent runs.\n" - ) - elif stage == 'model': - prompt = ( + "5. We hope to further reduce the total wirelength.\n" + ), + + 'model': ( f"**Stage: Model**\n" "In this stage, we decide how to model the optimization problem based on the data analysis.\n\n" - f"Data for modeling:\n{json.dumps(data, indent=2)}\n\n" + f"Data for modeling:\n{json.dumps(data, indent=2, default=str)}\n\n" "Please suggest:\n" "1. Appropriate modeling techniques.\n" "2. Key parameters to focus on.\n" "3. Surrogate model recommendations.\n" "4. Acquisition function choices.\n" - ) - elif stage == 'agglomerate': - prompt = ( + ), + + 'agglomerate': ( f"**Stage: Agglomerate**\n" "In this stage, we generate new parameter combinations to explore in the next optimization runs.\n\n" "Please provide a list of new parameter sets to try, ensuring they respect the domain constraints below.\n\n" @@ -291,181 +1464,394 @@ def _generate_llm_prompt(self, stage: str, data: Dict[str, Any]) -> str: "Each parameter set should be a dictionary with parameter names and their suggested values.\n" "**Important:** Make sure all parameter sets satisfy the domain constraints before suggesting them.\n" ) - else: - prompt = ( - f"**Stage: {stage.capitalize()}**\n" - f"Data:\n{json.dumps(data, indent=2)}\n\n" - "Please provide guidance based on the above data.\n" - ) + } + + stage_contexts = { + 'inspect': ( + f"metrics analyze: Total runs={data.get('log_data', {}).get('summary', {}).get('total_runs', 0)}, " + f"successful runs ={data.get('log_data', {}).get('summary', {}).get('successful_runs', 0)}" + ), + 'model': "Configure modeling methods based on inspection results", + 'agglomerate': "Configure parameter selection strategy based on modeling results" + } + + prompt = f"""**stages:{stage.upper()}** - return prompt + {stage_contexts.get(stage, '')} + + {tool_instructions.get(stage, '')} + + **Important: Use only tool calls and do not generate text replies!** + """ + + # ========= Splicing RAG ========= + rag_context = "" + if self.rag_model is not None and self.rag_embeddings is not None: + try: + print("[DEBUG] RAG: Starting retrieval...") + + # Step 1: Extract error information + error_summary = "" + if "log_data" in data: + all_errors = [] + for run in data["log_data"].get("runs", []): + if run.get("errors"): + all_errors.extend(run["errors"]) + if all_errors: + # Retrieve the most recent or frequent errors + top_errors = all_errors[-3:] # Last 3 posts + error_summary = "\n".join(top_errors) + print(f"[DEBUG] Detected {len(all_errors)} error messages. Sample:\n{error_summary}") + + # Step 2: Construct RAG query + if error_summary: + query = ( + f"Stage: {stage}. Objective: {self.objective}. " + f"The recent optimization runs failed with errors:\n{error_summary}\n\n" + "Retrieve relevant OpenROAD documentation, known failure modes, and " + "potential parameter tuning suggestions that may fix these issues." + ) + else: + query = ( + f"Stage: {stage}. Objective: {self.objective}. " + f"Focus on analyzing {stage}-related optimization results. " + f"Important metrics include wirelength, timing, area, and success rate. " + f"Find relevant OpenROAD documentation, parameter tuning guides, and failure pattern examples." + ) + + # Step 3: Execute search + rag_context = answerWithRAG( + query, + self.rag_embeddings, + self.rag_model, + self.rag_docs, + self.rag_docsDict, + ) + + if isinstance(rag_context, dict): # If returning dict + print(f"[DEBUG] RAG Retrieved {len(rag_context.get('docs', []))} related entries.") + for doc in rag_context.get("docs", [])[:3]: + print(f" ↳ {doc['title']} (score={doc['score']:.3f}) from {doc['source']}") + retrieved_text = rag_context.get("content", "") + else: + retrieved_text = rag_context + + # Step 4: add to prompt + if retrieved_text.strip(): + prompt += ( + "\n\n=== Retrieved OpenROAD Documentation (via RAG) ===\n" + f"{retrieved_text}\n" + "==============================================" + ) + print("[DEBUG] RAG: Context successfully added to prompt.") + else: + print("[DEBUG] RAG: Empty context retrieved.") + except Exception as e: + prompt += f"\n\n[WARN] RAG retrieval failed: {e}" + + if "log_data" in data: + all_errors = [] + for run in data["log_data"].get("runs", []): + if run.get("errors"): + all_errors.extend(run["errors"]) + + if all_errors: + error_summary = "\n".join(all_errors[-5:]) # The last 5 errors + prompt += f""" + + ### Detected Run Errors + {error_summary} + + The model must now act as an **EDA Debugging Assistant**. + Using the retrieved documentation and knowledge, analyze the errors above and: + 1. Identify the root causes of each error (e.g., tool misconfiguration, parameter overflow, timing issues, etc.) + 2. Suggest **specific parameter changes or flow adjustments** to prevent these errors. + 3. Indicate whether the error is likely due to constraints, routing congestion, or timing margin. + 4. Provide a short explanation for each suggestion. + + Output format: + Error Diagnosis: + - Root Cause: ... + - Recommended Fix: ... + - Suggested Parameter Change: ... + - Reason: ... + + """ + print("[DEBUG] Added error-fix section to prompt.") + def _collect_recent_errors(self, data: Dict[str, Any], max_errors=5) -> str: + errors = [] + for run in data.get("log_data", {}).get("runs", []): + if run.get("errors"): + errors.extend(run["errors"]) + print(f"[DEBUG] Found total {len(errors)} errors in all runs.") + return "\n".join(errors[-max_errors:]) if errors else "No errors detected." def _call_llm(self, stage: str, data: Dict[str, Any]) -> Dict[str, Any]: - """Call Claude to get recommendations for optimization parameters""" - print(f"\n=== Calling LLM for {stage} stage ===") - - # Hardcode API key - api_key = #PUT YOUR KEY HERE - - client = anthropic.Anthropic(api_key=api_key) - - tools = [ - { - "name": "configure_inspection", - "description": "Configure data inspection parameters", - "input_schema": { - "type": "object", - "properties": { - "n_clusters": { - "type": "integer", - "description": "Number of clusters for structure analysis", - "minimum": 2, - "maximum": 10 - }, - "correlation_threshold": { - "type": "number", - "description": "Threshold for considering correlations significant", - "minimum": 0, - "maximum": 1 - } - }, - "required": ["n_clusters", "correlation_threshold"] - } - }, - { - "name": "configure_model", - "description": "Configure modeling approach", - "input_schema": { - "type": "object", - "properties": { - "kernel_type": { - "type": "string", - "enum": ["rbf", "matern", "rational"], - "description": "Type of kernel to use" - }, - "preprocessing": { - "type": "string", - "enum": ["standard", "robust", "none"], - "description": "Type of preprocessing to apply" - }, - "acquisition": { - "type": "string", - "enum": ["ei", "ucb", "pi"], - "description": "Acquisition function to use" - }, - "surrogate_weight": { - "type": "number", - "description": "Weight to give surrogate values", - "minimum": 0, - "maximum": 1 - } - }, - "required": ["kernel_type", "preprocessing", "acquisition", "surrogate_weight"] - } - }, - { - "name": "configure_selection", - "description": "Configure point selection strategy", - "input_schema": { - "type": "object", - "properties": { - "method": { - "type": "string", - "enum": ["entropy", "kmeans", "hybrid", "graph"], - "description": "Selection method to use" - }, - "quality_weight": { - "type": "number", - "description": "Weight between quality and diversity", - "minimum": 0, - "maximum": 1 - }, - "uncertainty_bonus": { - "type": "number", - "description": "Weight for uncertainty in quality scores", - "minimum": 0, - "maximum": 1 - } - }, - "required": ["method", "quality_weight", "uncertainty_bonus"] - } + # """Call Claude to get recommendations for optimization parameters""" + # print(f"\n=== Calling LLM for {stage} stage ===") + """Call LLM to get recommendations for optimization parameters using react framework""" + print(f"\n=== Calling LLM with ReAct framework for {stage} stage ===") + + try: + react_prompt = self._generate_react_prompt(stage, data) + print(f"Generated prompt with context for {stage}") + print("=== Context Message ===") + print(react_prompt) + print("========================") + available_tools = self._create_react_tools(stage, data) + + react_result = self.react_framework.run_react_cycle( + initial_prompt=react_prompt, + available_tools=available_tools, + max_steps=3, + temperature=0.1 + ) + # === If an error occurs, enter Debug mode === + if "log_data" in data and any(run.get("errors") for run in data["log_data"].get("runs", [])): + print("\n[DEBUG] Detected errors in previous runs. Invoking Debug Assistant mode...") + + # Collect error information + all_errors = [] + for run in data["log_data"]["runs"]: + if run.get("errors"): + all_errors.extend(run["errors"]) + error_text = "\n".join(all_errors[-5:]) # Recent entries + + # Construct a Debug Prompt + debug_prompt = f""" + You are now an **EDA Debugging Expert**. + Based on the following OpenROAD errors and RAG documentation, analyze and provide concrete repair suggestions. + + Errors Detected: + {error_text} + + Please identify: + 1. Root cause of each error. + 2. Specific parameter changes (e.g., in floorplan, CTS, or routing stages) that could fix the issue. + 3. Whether this issue is due to timing, congestion, or setup misconfiguration. + 4. One short explanation per fix. + + Return your answer in **JSON format** like: + {{ + "error_analysis": [ + {{ + "error": "...", + "cause": "...", + "fix": "...", + "params_to_adjust": {{"param_name": "new_value"}} + }} + ] + }} + """ + + # Call LLM to output repair suggestions + debug_result = self.react_framework.run_react_cycle( + initial_prompt=debug_prompt, + available_tools=available_tools, + max_steps=2, + temperature=0.2 + ) + + print("\n[DEBUG] LLM Debug Assistant Result:") + print(debug_result.get("final_answer", "")) + + # Save repair suggestions to the main results + react_result["error_fix_suggestions"] = debug_result.get("final_answer", "") + # Write files for manual viewing + with open("logs/error_fix_suggestions.json", "w") as f: + f.write(debug_result.get("final_answer", "")) + print(f"\n=== ReAct Cycle Completed ===") + print(f"Completed steps: {react_result.get('completed_steps', 0)}/{react_result.get('max_steps', 8)}") + print(f"Final Answer: {react_result['final_answer']}") + + configs = self._parse_react_final_answer(react_result["final_answer"], stage) + + if react_result.get('reasoning_history'): + print(f"\n=== Reasoning History ({len(react_result['reasoning_history'])} steps) ===") + for step in react_result['reasoning_history']: + print(f"Step {step['step']}: {step.get('thought', 'No thought')}") + + print(f"Returning config for stage '{stage}': {configs}") + return configs + + except Exception as e: + print(f"Error in LLM call for stage {stage}: {e}") + default_config = { + 'inspect': {"n_clusters": 5, "correlation_threshold": 0.5}, + 'model': {"kernel_type": "matern", "preprocessing": "robust", + "acquisition": "ei", "surrogate_weight": 0.8}, + 'agglomerate': {"method": "hybrid", "quality_weight": 0.7, + "uncertainty_bonus": 0.2} } - ] + return default_config.get(stage, {}) + - # Get data summaries - if stage == 'inspect': - print("Generating data distribution and structure summaries...") - # Extract X and Y from successful runs if available - X = [] - Y = [] - if 'log_data' in data and 'runs' in data['log_data']: - for run in data['log_data']['runs']: - if run['success'] and 'metrics' in run: - obj = self._calculate_objective(run) - if obj['value'] is not None or obj['surrogate'] is not None: - # Use parameters as X - params = [] - for param in self.param_constraints.keys(): - params.append(float(run.get('parameters', {}).get(param, 0))) - X.append(params) - # Use objective as Y - Y.append(obj['value'] if obj['value'] is not None else obj['surrogate']) - - if X and Y: - dist_summary = inspect_data_distribution(np.array(X), np.array(Y)) - struct_summary = inspect_data_structure(np.array(X)) - else: - print("No successful runs found, using empty summaries") - dist_summary = {} - struct_summary = {} + def _generate_react_prompt(self, stage: str, data: Dict[str, Any]) -> str: + """generate prompts of ReAct framework""" + + stage_descriptions = { + 'inspect': ( + "You are an expert EDA optimization analyst. Analyze the optimization run data to identify patterns " + "and insights. Use the available tools to examine data distributions, correlations, and successful " + "parameter ranges. Your goal is to understand what makes runs successful and provide recommendations " + "for the modeling stage." + ), + 'model': ( + "You are an expert machine learning engineer for EDA optimization. Based on the inspection results, " + "configure the modeling approach for Bayesian optimization. Consider kernel selection, acquisition " + "functions, and surrogate modeling strategies. Balance exploration and exploitation based on the data." + ), + 'agglomerate': ( + "You are an expert parameter optimization specialist. Generate new parameter combinations for the " + "next optimization iteration. Use insights from previous stages to focus on promising regions while " + "maintaining diversity. Ensure all parameters satisfy the domain constraints." + ) + } + + constraints_text = "Parameter Constraints:\n" + for param, info in self.param_constraints.items(): + constraints_text += f"- {param} ({info['type']}, range: {info['range']})\n" + + react_format_instructions = """ +**ReAct Framework Instructions - MUST FOLLOW THIS FORMAT:** + +1. **Thought**: Analyze the current situation and decide what to do next +2. **Action**: Choose one tool from the available tools +3. **Action Input**: Provide the appropriate input for the chosen tool +4. **Observation**: Wait for the tool's response, then continue reasoning + +**Available Tools**: You have access to various analysis tools. Use them to gather information before making decisions. + +**DO NOT include Final Answer until you have completed all necessary analysis.** +**DO NOT predict or simulate tool observations.** +**You will receive actual Observation from tools before continuing.** + +Only after proper analysis: +**Final Answer Format**: Only when you have completed your analysis, provide: +Final Answer: {your_configuration_here} + +**Example**: +Thought: I need to understand the data patterns first. Let me analyze the success rates. +Action: analyze_data_patterns +Action Input: {} +Observation: [Tool response...] +Thought: Now I need to check parameter correlations... +Action: analyze_correlations +Action Input: {} +Observation: [Tool response...] +Final Answer: {"n_clusters": 5, "correlation_threshold": 0.7} +""" + + prompt = f""" + {stage_descriptions[stage]} + + **Current Stage**: {stage.upper()} + **Objective**: {self.objective} + **Platform**: {self.platform} + **Design**: {self.design} + + **Available Data**: + - Total runs: {data.get('log_data', {}).get('summary', {}).get('total_runs', 0)} + - Successful runs: {data.get('log_data', {}).get('summary', {}).get('successful_runs', 0)} + - Failed runs: {data.get('log_data', {}).get('summary', {}).get('failed_runs', 0)} + + {constraints_text} + {react_format_instructions} + + Begin your analysis: + """ + + rag_context = "" + # ======== extract errors ======== + error_summary = self._collect_recent_errors(data) + if error_summary and "No errors" not in error_summary: + print("[DEBUG] RAG: Detected error summary, adding error analysis prompt...") + prompt += f""" + + ### Detected Run Errors + {error_summary} + + You are now acting as an **EDA Debugging Assistant**. + Analyze the errors above and: + 1. Identify the root causes. + 2. Suggest specific parameter changes. + 3. Indicate whether the error is due to timing, routing, or constraints. + 4. Provide short explanations for each. + + Output format: + Error Diagnosis: + - Root Cause: ... + - Recommended Fix: ... + - Suggested Parameter Change: ... + - Reason: ... + """ else: - dist_summary = {} - struct_summary = {} - - # Generate context message - context_message = self._generate_llm_prompt(stage, data) - print(f"Generated prompt with context for {stage}") - - print("Making LLM API call...") - response = client.messages.create( - model="claude-3-sonnet-20240229", - max_tokens=2048, - tools=tools, - messages=[{ - "role": "user", - "content": context_message - }] - ) + print("[DEBUG] No errors found in logs for this stage.") + if self.rag_model is not None and self.rag_embeddings is not None: + try: + print("[DEBUG] RAG: Starting retrieval...") + query = ( + f"Stage: {stage}. Objective: {self.objective}. " + f"Focus on analyzing {stage}-related optimization results. " + f"Important metrics include wirelength, timing, area, and success rate. " + f"Find relevant OpenROAD documentation, parameter tuning guides, and failure pattern examples." + ) + rag_context = answerWithRAG( + query, + self.rag_embeddings, + self.rag_model, + self.rag_docs, + self.rag_docsDict + ) + print(f"[DEBUG] RAG: Retrieved context length = {len(rag_context)}") + if rag_context.strip(): + prompt += ( + "\n\n=== Retrieved OpenROAD Documentation (via RAG) ===\n" + f"{rag_context}\n" + "==============================================" + ) + print("[DEBUG] RAG: Context successfully added to prompt.") + else: + print("[DEBUG] RAG: Empty context retrieved.") + except Exception as e: + prompt += f"\n\n[WARN] RAG retrieval failed: {e}" - # Extract configurations + return prompt + + def _parse_react_final_answer(self, final_answer: str, stage: str) -> Dict[str, Any]: + """parse react final answer""" + + default_configs = { + 'inspect': {"n_clusters": 5, "correlation_threshold": 0.5}, + 'model': {"kernel_type": "matern", "preprocessing": "robust", + "acquisition": "ei", "surrogate_weight": 0.8}, + 'selection': {"method": "hybrid", "quality_weight": 0.7, + "uncertainty_bonus": 0.2} + } + configs = {} - print("\nReceived tool calls from LLM:") - for block in response.content: - if block.type == 'tool_use': - print(f"- {block.name}: {block.input}") - if block.name == 'configure_inspection': - configs['inspection'] = block.input - elif block.name == 'configure_model': - configs['model'] = block.input - elif block.name == 'configure_selection': - configs['selection'] = block.input - - # Add default configs if missing - for key, default in [ - ('inspection', {"n_clusters": 5, "correlation_threshold": 0.5}), - ('model', {"kernel_type": "matern", "preprocessing": "robust", - "acquisition": "ei", "surrogate_weight": 0.8}), - ('selection', {"method": "hybrid", "quality_weight": 0.7, - "uncertainty_bonus": 0.2}) - ]: - if key not in configs: - print(f"Warning: No {key} config from LLM, using defaults: {default}") - configs[key] = default + + if final_answer and "Reached maximum steps" not in final_answer: + try: + json_match = re.search(r'\{.*\}', final_answer, re.DOTALL) + if json_match: + extracted_config = json.loads(json_match.group()) + configs[stage] = extracted_config + print(f"✓ Extracted configuration from ReAct response: {extracted_config}") + else: + configs[stage] = default_configs.get(stage, {}) + print(f"⚠ Using default configuration for {stage} stage") + except Exception as e: + print(f"Error parsing ReAct final answer: {e}") + configs[stage] = default_configs.get(stage, {}) + else: + configs[stage] = default_configs.get(stage, {}) + print(f"ReAct failed to produce answer, using default for {stage}") return configs def run_iteration(self, num_runs: int) -> None: - """Run a complete iteration of the optimization workflow""" + """Run a complete iteration of the optimization workflow using react framework""" print(f"\n=== Starting optimization iteration for {self.platform}/{self.design} ===") print(f"Objective: {self.objective}") print(f"Number of runs requested: {num_runs}") @@ -477,25 +1863,29 @@ def run_iteration(self, num_runs: int) -> None: f"{log_data['summary']['successful_runs']} successful") # Get LLM recommendations for inspection and analysis - print("\nGetting LLM recommendations for inspection...") + # print("\nGetting LLM recommendations for inspection...") + print("\nGetting LLM recommendations with ReAct framework for inspection...") inspect_configs = self._call_llm('inspect', { 'log_data': log_data, 'initial_params': self.initial_params, 'sdc_context': self.sdc_context }) - print(f"LLM inspection config: {inspect_configs['inspection']}") + inspection_config = inspect_configs.get('inspect', {}) + print(f"React inspection config: {inspection_config}") # Step 2: Analyze metrics with LLM config - print("\nStep 2: Analyzing metrics...") + print("\nStep 2: Analyzing metrics ...") metrics = self.analyze_metrics( log_data, - n_clusters=inspect_configs['inspection']['n_clusters'], - correlation_threshold=inspect_configs['inspection']['correlation_threshold'] + # n_clusters=inspect_configs['inspection']['n_clusters'], + n_clusters=inspection_config.get('n_clusters', 5), + # correlation_threshold=inspect_configs['inspection']['correlation_threshold'] + correlation_threshold=inspection_config.get('correlation_threshold', 0.5) ) print(f"Processed metrics for {len(metrics.get('objectives', []))} successful runs") - # Get LLM recommendations for modeling based on inspection results - print("\nGetting LLM recommendations for modeling...") + # Get LLM recommendations for modeling based on inspection results with ReAct framework + print("\nGetting LLM recommendations with ReAct framework for modeling...") model_configs = self._call_llm('model', { 'log_data': log_data, 'metrics': metrics, @@ -503,20 +1893,25 @@ def run_iteration(self, num_runs: int) -> None: 'sdc_context': self.sdc_context, 'inspection_results': inspect_configs }) - print(f"LLM model config: {model_configs['model']}") + model_config = model_configs.get('model', {}) + print(f"LLM model config: {model_config}") # Step 3: Evaluate models with LLM config print("\nStep 3: Evaluating models...") model_results = self.evaluate_models( log_data, metrics, - kernel_type=model_configs['model']['kernel_type'], - preprocessing=model_configs['model']['preprocessing'], - acquisition=model_configs['model']['acquisition'], - surrogate_weight=model_configs['model']['surrogate_weight'] + # kernel_type=model_configs['model']['kernel_type'], + model_config.get('kernel_type', 'matern'), + # preprocessing=model_configs['model']['preprocessing'], + preprocessing=model_config.get('preprocessing', 'robust'), + # acquisition=model_configs['model']['acquisition'], + acquisition=model_config.get('acquisition', 'ei'), + # surrogate_weight=model_configs['model']['surrogate_weight'] + surrogate_weight=model_config.get('surrogate_weight', 0.8) ) - # Get LLM recommendations for parameter selection based on all previous results - print("\nGetting LLM recommendations for parameter selection...") + # Get LLM recommendations for parameter selection based on all previous results with ReAct framework + print("\nGetting LLM recommendations with ReAct framework for parameter selection...") selection_configs = self._call_llm('agglomerate', { 'log_data': log_data, 'metrics': metrics, @@ -526,20 +1921,26 @@ def run_iteration(self, num_runs: int) -> None: 'inspection_results': inspect_configs, 'model_configs': model_configs }) - print(f"LLM selection config: {selection_configs['selection']}") + selection_config = selection_configs.get('agglomerate', {}) + print(f"LLM selection config: {selection_config}") # Step 4: Generate parameters with LLM config print("\nStep 4: Generating parameters...") self.generate_parameters( log_data, metrics, model_results, num_runs, - selection_method=selection_configs['selection']['method'], - quality_weight=selection_configs['selection']['quality_weight'], - uncertainty_bonus=selection_configs['selection']['uncertainty_bonus'] + # selection_method=selection_configs['selection']['method'], + # quality_weight=selection_configs['selection']['quality_weight'], + # uncertainty_bonus=selection_configs['selection']['uncertainty_bonus'] + selection_method=selection_config.get('method', 'hybrid'), + quality_weight=selection_config.get('quality_weight', 0.7), + uncertainty_bonus=selection_config.get('uncertainty_bonus', 0.2) ) - + def inspect_logs(self) -> Dict[str, Any]: - """Step 1: Inspect all logs so far""" - log_dir = f"logs/{self.platform}/{self.design}" + """Step 1: Inspect all .log and .json logs recursively""" + log_dir = "logs" + pattern = f"{self.platform}_{self.design}_run" + log_data = { 'runs': [], 'summary': { @@ -548,25 +1949,62 @@ def inspect_logs(self) -> Dict[str, Any]: 'failed_runs': 0 } } - - # Ensure log directory exists + if not os.path.exists(log_dir): return log_data - - # Process each log file - for log_file in os.listdir(log_dir): - if log_file.endswith('.log'): - run_data = process_log_file(os.path.join(log_dir, log_file)) - log_data['runs'].append(run_data) - - # Update summary - log_data['summary']['total_runs'] += 1 - if run_data['success']: - log_data['summary']['successful_runs'] += 1 - else: - log_data['summary']['failed_runs'] += 1 - + + run_groups = {} + + for root, _, files in os.walk(log_dir): + for log_file in files: + if log_file.endswith(('.log', '.json')): + log_path = os.path.join(root, log_file) + + if log_file.startswith(pattern) or (self.platform in root and self.design in root): + + run_id = "main" + m = re.search(r'_run(\d+)\.log$', log_file) + if m: + run_id = f"base_{m.group(1)}" + + elif 'base_' in root: + run_id = os.path.basename(root) + + run_data = process_log_file(log_path) + + if run_id not in run_groups: + run_groups[run_id] = { + 'run_id': run_id, + 'success': True, + 'metrics': {}, + 'errors': [], + 'files': [] + } + + run_groups[run_id]['success'] &= run_data.get('success', True) + run_groups[run_id]['files'].append(log_path) + + if 'metrics' in run_data and run_data['metrics']: + run_groups[run_id]['metrics'].update(run_data['metrics']) + + if 'errors' in run_data and run_data['errors']: + run_groups[run_id]['errors'].extend(run_data['errors']) + + for run_id, run_data in run_groups.items(): + print(f"DEBUG: Run {run_id} success: {run_data['success']}") + print(f"DEBUG: Run {run_id} metrics: {run_data['metrics']}") + print(f"DEBUG: Run {run_id} errors: {run_data['errors']}") + print(f"DEBUG: Run {run_id} files: {run_data['files']}") + + log_data['runs'].append(run_data) + log_data['summary']['total_runs'] += 1 + if run_data['success']: + log_data['summary']['successful_runs'] += 1 + else: + log_data['summary']['failed_runs'] += 1 + return log_data + def analyze_metrics(self, log_data: Dict[str, Any], n_clusters: int, correlation_threshold: float) -> Dict[str, Any]: """Step 2: Analyze metrics from log data with improved analysis""" @@ -658,6 +2096,7 @@ def analyze_metrics(self, log_data: Dict[str, Any], n_clusters: int, correlation return metrics + def evaluate_models(self, log_data: Dict[str, Any], metrics: Dict[str, Any], kernel_type: str, preprocessing: str, acquisition: str, surrogate_weight: float) -> Dict[str, Any]: """Step 3: Use improved model functions to evaluate parameter quality""" @@ -1053,4 +2492,4 @@ def main(): workflow.run_iteration(num_runs) # Use the run_iteration method instead of individual steps if __name__ == "__main__": - main() \ No newline at end of file + main() From 026f05e2c57db26b9affe53348657b41c08efef0 Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:30:26 +0800 Subject: [PATCH 03/42] Update optimize.py --- flow-Agent/optimize.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/flow-Agent/optimize.py b/flow-Agent/optimize.py index fecf05f..630c2e0 100644 --- a/flow-Agent/optimize.py +++ b/flow-Agent/optimize.py @@ -415,7 +415,7 @@ def __init__(self, platform: str, design: str, objective: str): self.react_framework = ReActFramework( client=OpenAI( base_url="https://ai.gitee.com/v1", - api_key=" ", + api_key= #PUT YOUR KEY HERE, ), model_name="DeepSeek-V3" ) From 2296adeed33ecb526c3890e8d9401d1343f155ce Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:31:21 +0800 Subject: [PATCH 04/42] Create stage_optimize.py --- flow-Agent/stage_optimize.py | 528 +++++++++++++++++++++++++++++++++++ 1 file changed, 528 insertions(+) create mode 100644 flow-Agent/stage_optimize.py diff --git a/flow-Agent/stage_optimize.py b/flow-Agent/stage_optimize.py new file mode 100644 index 0000000..a52efd3 --- /dev/null +++ b/flow-Agent/stage_optimize.py @@ -0,0 +1,528 @@ +#!/usr/bin/env python3 +""" +Stage-level optimization driver for OpenROAD Flow Scripts. + +This tool executes the OpenROAD flow one stage at a time (synth → floorplan → place → cts → route → finish), +collects the resulting metrics/logs, and queries the existing ReAct framework to recommend +stage-local parameter tuning. +""" + +from __future__ import annotations + +import argparse +import json +import os +import re +import statistics +import subprocess +import sys +import textwrap +from dataclasses import dataclass, field +from pathlib import Path +from typing import Any, Dict, Iterable, List, Optional, Tuple + +from optimize import ( + OptimizationWorkflow, + process_log_file, +) + + +@dataclass +class StageDefinition: + """Metadata describing how to run and analyse a single flow stage.""" + + name: str + make_target: str + log_prefix: str + description: str + parameter_keys: List[str] = field(default_factory=list) + + +# Mapping between parameter identifiers used in OptimizationWorkflow and their make/env names. +PARAM_TO_ENV_VAR = { + "synth_flatten": "SYNTH_FLATTEN", + "core_util": "CORE_UTILIZATION", + "cell_pad_global": "CELL_PAD_IN_SITES_GLOBAL_PLACEMENT", + "cell_pad_detail": "CELL_PAD_IN_SITES_DETAIL_PLACEMENT", + "lb_addon": "PLACE_DENSITY_LB_ADDON", + "enable_dpo": "ENABLE_DPO", + "pin_layer": "PIN_LAYER_ADJUST", + "above_layer": "ABOVE_LAYER_ADJUST", + "tns": "TNS_END_PERCENT", + "cts_size": "CTS_CLUSTER_SIZE", + "cts_diameter": "CTS_CLUSTER_DIAMETER", +} + + +def _stage_definitions() -> List[StageDefinition]: + """Return the default stage ordering and configuration.""" + return [ + StageDefinition( + name="synth", + make_target="do-synth", + log_prefix="1_", + description="Logic synthesis using Yosys; focus on timing slack and area metrics.", + parameter_keys=["synth_flatten"], + ), + StageDefinition( + name="floorplan", + make_target="do-floorplan", + log_prefix="2_", + description="Macro and core floorplanning; adjust area utilization and pin placement.", + parameter_keys=[ + "core_util", + "cell_pad_global", + "cell_pad_detail", + "lb_addon", + ], + ), + StageDefinition( + name="place", + make_target="do-place", + log_prefix="3_", + description="Global/detail placement; tune density, legalization and detail placement options.", + parameter_keys=[ + "lb_addon", + "enable_dpo", + "pin_layer", + "above_layer", + ], + ), + StageDefinition( + name="cts", + make_target="do-cts", + log_prefix="4_", + description="Clock-tree synthesis (CTS); control cluster sizing and clock routing targets.", + parameter_keys=[ + "cts_size", + "cts_diameter", + ], + ), + StageDefinition( + name="route", + make_target="do-route", + log_prefix="5_", + description="Global and detailed routing; focus on timing violations and routing congestion.", + parameter_keys=[ + "pin_layer", + "above_layer", + "tns", + ], + ), + StageDefinition( + name="finish", + make_target="do-finish", + log_prefix="6_", + description="Fill, reporting and final sign-off data generation.", + parameter_keys=[], + ), + ] + + +class StageOptimizationDriver: + """Coordinates per-stage execution, log aggregation, and ReAct-based recommendations.""" + + def __init__( + self, + platform: str, + design: str, + objective: str, + stages: Optional[Iterable[str]] = None, + max_react_steps: int = 3, + temperature: float = 0.1, + workdir: Optional[Path] = None, + dry_run: bool = False, + ) -> None: + self.workdir = Path(workdir or os.getcwd()) + self.platform = platform + self.design = design + self.objective = objective.upper() + self.max_react_steps = max_react_steps + self.temperature = temperature + self.dry_run = dry_run + + # Reuse existing workflow components (embeddings, constraints, ReAct client, etc.). + self.workflow = OptimizationWorkflow(platform, design, objective) + self.react = self.workflow.react_framework + self.initial_params = self.workflow.initial_params + self.param_constraints = self.workflow.param_constraints + + # Track per-stage overrides/recommendations. + self.stage_overrides: Dict[str, Dict[str, Any]] = {} + self.stage_recommendations: Dict[str, Dict[str, Any]] = {} + + stage_list = _stage_definitions() + if stages: + stage_filter = {name.lower() for name in stages} + stage_list = [sd for sd in stage_list if sd.name.lower() in stage_filter] + missing = stage_filter.difference({sd.name.lower() for sd in stage_list}) + if missing: + raise ValueError(f"Unknown stages requested: {', '.join(sorted(missing))}") + + self.stage_sequence = stage_list + + # ------------------------------------------------------------------ CLI helpers + def run(self) -> None: + for stage in self.stage_sequence: + self._execute_stage(stage) + + self._print_summary() + + # ------------------------------------------------------------------ Execution + def _execute_stage(self, stage: StageDefinition) -> None: + print(f"\n=== Stage: {stage.name.upper()} ===") + print(stage.description) + + overrides = self.stage_overrides.get(stage.name, {}) + if overrides: + print("Applying overrides:", " ".join(f"{k}={v}" for k, v in overrides.items())) + + command = ["make", stage.make_target] + for env_var, value in overrides.items(): + command.append(f"{env_var}={value}") + + if self.dry_run: + print("(dry-run) Skipping execution:", " ".join(command)) + else: + print("Running:", " ".join(command)) + try: + subprocess.run( + command, + cwd=self.workdir, + check=True, + ) + except subprocess.CalledProcessError as exc: + print(f"[ERROR] Stage '{stage.name}' execution failed with exit code {exc.returncode}") + raise + + stage_data = self._collect_stage_data(stage) + parameter_info = self._get_stage_parameter_info(stage) + + if not parameter_info: + print("No adjustable parameters registered for this stage; skipping ReAct recommendation.") + return + + react_prompt = self._build_stage_prompt(stage, stage_data, parameter_info) + tools = self._build_stage_tools(stage_data, parameter_info) + + print("[INFO] Requesting ReAct recommendations...") + react_result = self.react.run_react_cycle( + initial_prompt=react_prompt, + available_tools=tools, + max_steps=self.max_react_steps, + temperature=self.temperature, + ) + + final_answer = react_result.get("final_answer", "") + recommendations = self._parse_stage_recommendations(stage, final_answer, parameter_info) + if recommendations: + self.stage_recommendations[stage.name] = recommendations + print("[INFO] Recommended adjustments:") + for env_var, value in recommendations.items(): + print(f" - {env_var} := {value}") + else: + print("[WARN] No actionable recommendations parsed from ReAct response.") + + # ------------------------------------------------------------------ Data aggregation + def _collect_stage_data(self, stage: StageDefinition) -> Dict[str, Any]: + log_dir = self.workdir / "logs" + log_files = sorted(log_dir.glob(f"{stage.log_prefix}*.log")) + json_files = sorted(log_dir.glob(f"{stage.log_prefix}*.json")) + + log_summaries = [] + aggregated_metrics: Dict[str, List[float]] = {} + errors: List[str] = [] + + for log_file in log_files: + summary = process_log_file(str(log_file)) + summary["path"] = str(log_file) + log_summaries.append(summary) + + for metric_name, value in summary.get("metrics", {}).items(): + try: + aggregated_metrics.setdefault(metric_name, []).append(float(value)) + except (TypeError, ValueError): + continue + + errors.extend(summary.get("errors", [])) + + aggregated = { + metric: { + "mean": statistics.mean(values) if values else None, + "min": min(values) if values else None, + "max": max(values) if values else None, + "latest": values[-1] if values else None, + "samples": len(values), + } + for metric, values in aggregated_metrics.items() + } + + json_payloads: List[Tuple[str, Any]] = [] + for json_file in json_files: + try: + with open(json_file, "r", encoding="utf-8") as f: + data = json.load(f) + json_payloads.append((str(json_file), data)) + except Exception as exc: # noqa: BLE001 + errors.append(f"Failed to parse {json_file}: {exc}") + + recent_log_snippet = "" + if log_files: + recent_log_snippet = self._tail_file(log_files[-1], max_lines=40) + + return { + "logs": log_summaries, + "metrics": aggregated, + "json": json_payloads, + "errors": errors, + "recent_log_snippet": recent_log_snippet, + } + + def _get_stage_parameter_info(self, stage: StageDefinition) -> List[Dict[str, Any]]: + info: List[Dict[str, Any]] = [] + for param_key in stage.parameter_keys: + env_var = PARAM_TO_ENV_VAR.get(param_key) + constraint = self.param_constraints.get(param_key) + if env_var is None or constraint is None: + continue + + current_value = self._current_env_value(stage.name, env_var, constraint) + info.append( + { + "param_key": param_key, + "env_var": env_var, + "type": constraint.get("type"), + "range": constraint.get("range"), + "current_value": current_value, + } + ) + + return info + + # ------------------------------------------------------------------ Prompt + tools + def _build_stage_prompt( + self, + stage: StageDefinition, + stage_data: Dict[str, Any], + parameter_info: List[Dict[str, Any]], + ) -> str: + metrics_lines = [] + for name, stats in stage_data["metrics"].items(): + metrics_lines.append( + f"- {name}: latest={stats['latest']} mean={stats['mean']} min={stats['min']} max={stats['max']} (samples={stats['samples']})" + ) + metrics_text = "\n".join(metrics_lines) if metrics_lines else "No metrics captured for this stage." + + parameters_text = json.dumps(parameter_info, indent=2) + + errors_text = "\n".join(stage_data.get("errors", [])) or "No errors captured." + log_tail = stage_data.get("recent_log_snippet", "").strip() or "(no log excerpt available)" + + prompt = textwrap.dedent( + f""" + You are assisting with stage-specific optimization of the OpenROAD flow. + + Stage: {stage.name.upper()} + Platform: {self.platform} + Design: {self.design} + Objective: {self.objective} + + Stage description: + {stage.description} + + Recent metrics: + {metrics_text} + + Errors (if any): + {errors_text} + + Recent log excerpt: + ``` + {log_tail} + ``` + + Adjustable parameters for this stage (env vars with ranges and current values): + {parameters_text} + + Requirements: + - Suggest updated values only for the listed parameters. + - Keep all values within the specified ranges and respect their types. + - Focus on improving the stage metrics relevant to the {self.objective} objective. + - Return concise recommendations ready to be passed back to `make` as VAR=value overrides. + + Final Answer format (must be JSON): + Final Answer: {{"parameters": {{"ENV_VAR": value, ...}}, "notes": "short justification"}} + """ + ).strip() + return prompt + + def _build_stage_tools( + self, + stage_data: Dict[str, Any], + parameter_info: List[Dict[str, Any]], + ) -> Dict[str, Any]: + return { + "list_parameters": lambda _: json.dumps(parameter_info, indent=2), + "show_metrics": lambda _: json.dumps(stage_data.get("metrics", {}), indent=2), + "show_errors": lambda _: "\n".join(stage_data.get("errors", [])) or "No errors recorded.", + "show_log_tail": lambda _: stage_data.get("recent_log_snippet", "") or "No log excerpt.", + } + + # ------------------------------------------------------------------ Parsing + helpers + def _parse_stage_recommendations( + self, + stage: StageDefinition, + final_answer: str, + parameter_info: List[Dict[str, Any]], + ) -> Dict[str, Any]: + if not final_answer or "Final Answer" not in final_answer: + return {} + + match = re.search(r"\{.*\}", final_answer, re.DOTALL) + if not match: + return {} + + try: + payload = json.loads(match.group()) + except json.JSONDecodeError: + return {} + + raw_params = payload.get("parameters", payload) + if not isinstance(raw_params, dict): + return {} + + valid_envs = {info["env_var"] for info in parameter_info} + key_to_env = {info["param_key"]: info["env_var"] for info in parameter_info} + recommendations: Dict[str, Any] = {} + + for key, value in raw_params.items(): + env_var = key if key in valid_envs else key_to_env.get(key.lower()) or key_to_env.get(key) + if env_var not in valid_envs: + continue + + constraint = self._constraint_for_env(env_var, parameter_info) + coerced = self._coerce_to_constraint(value, constraint) + if coerced is not None: + recommendations[env_var] = coerced + + return recommendations + + def _constraint_for_env(self, env_var: str, parameter_info: List[Dict[str, Any]]) -> Optional[Dict[str, Any]]: + for info in parameter_info: + if info["env_var"] == env_var: + return { + "type": info.get("type"), + "range": info.get("range"), + } + return None + + def _coerce_to_constraint(self, value: Any, constraint: Optional[Dict[str, Any]]) -> Optional[Any]: + if constraint is None: + return value + + value_type = constraint.get("type") + value_range = constraint.get("range") + + try: + if value_type == "int": + coerced: Any = int(round(float(value))) + elif value_type == "float": + coerced = float(value) + else: + coerced = value + except (TypeError, ValueError): + return None + + if value_range and len(value_range) == 2: + min_val, max_val = value_range + if isinstance(coerced, (int, float)): + coerced = max(min_val, min(max_val, coerced)) + + return coerced + + def _current_env_value(self, stage_name: str, env_var: str, constraint: Dict[str, Any]) -> Any: + if stage_name in self.stage_overrides and env_var in self.stage_overrides[stage_name]: + return self.stage_overrides[stage_name][env_var] + + raw_value = self.initial_params.get(env_var) + if raw_value is None: + raw_value = os.environ.get(env_var) + + if raw_value is None: + return None + + return self._coerce_to_constraint(raw_value, constraint) + + @staticmethod + def _tail_file(path: Path, max_lines: int = 40) -> str: + try: + with open(path, "r", encoding="utf-8", errors="ignore") as f: + lines = f.readlines() + return "".join(lines[-max_lines:]) + except OSError: + return "" + + def _print_summary(self) -> None: + if not self.stage_recommendations: + print("\nNo stage recommendations were produced.") + return + + print("\n=== Stage Recommendations Summary ===") + for stage_name, params in self.stage_recommendations.items(): + print(f"{stage_name.upper()}:") + for env_var, value in params.items(): + print(f" - {env_var} := {value}") + + +def parse_args(argv: Optional[List[str]] = None) -> argparse.Namespace: + parser = argparse.ArgumentParser( + description="Run stage-by-stage optimization flow with ReAct recommendations.", + ) + parser.add_argument("platform", help="PDK/platform name (e.g. asap7, sky130hd).") + parser.add_argument("design", help="Design name (e.g. aes, ibex).") + parser.add_argument("objective", help="Optimization objective (ECP, DWL, COMBO).") + parser.add_argument( + "--stages", + nargs="+", + default=None, + help="Subset of stages to run (default: all). Options: synth floorplan place cts route finish.", + ) + parser.add_argument( + "--max-react-steps", + type=int, + default=3, + help="Maximum reasoning steps for the ReAct loop.", + ) + parser.add_argument( + "--temperature", + type=float, + default=0.1, + help="Sampling temperature for the LLM.", + ) + parser.add_argument( + "--dry-run", + action="store_true", + help="Show the make commands without executing them.", + ) + + return parser.parse_args(argv) + + +def main(argv: Optional[List[str]] = None) -> None: + args = parse_args(argv) + + driver = StageOptimizationDriver( + platform=args.platform, + design=args.design, + objective=args.objective, + stages=args.stages, + max_react_steps=args.max_react_steps, + temperature=args.temperature, + dry_run=args.dry_run, + ) + driver.run() + + +if __name__ == "__main__": + main() + From 70e734986e0ac05b061648bbceed08226a7ab21c Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:34:35 +0800 Subject: [PATCH 05/42] Create test_rag.py --- flow-Agent/test_rag.py | 63 ++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 63 insertions(+) create mode 100644 flow-Agent/test_rag.py diff --git a/flow-Agent/test_rag.py b/flow-Agent/test_rag.py new file mode 100644 index 0000000..5914d10 --- /dev/null +++ b/flow-Agent/test_rag.py @@ -0,0 +1,63 @@ +import os +import torch +from sentence_transformers import SentenceTransformer +from rag.index import load_embeddings_and_docs, build_and_save_embeddings +from rag.util import answerWithRAG +from pathlib import Path + +def test_rag(query): + """ + Test the RAG retrieval and response functions. + """ + print("=" * 60) + print("[TEST] Starting RAG Functionality Test") + print("=" * 60) + + # Make sure RAGData exists + if not os.path.exists("rag_date"): + os.makedirs("rag_date", exist_ok=True) + + # Step 1: Build if the embeddings do not exist + emb_path = os.path.join("rag_date", "embeddings.npy") + docs_path = os.path.join("rag_date", "docs.pkl") + + if not os.path.exists(emb_path) or not os.path.exists(docs_path): + print("[INFO] Embeddings not found, building new ones...") + build_and_save_embeddings() + else: + print("[INFO] Embeddings found, skipping build step.") + + # Step 2: Load vector library + print("[INFO] Loading embeddings and documents...") + embeddings_np, docs, docsDict = load_embeddings_and_docs() + embeddings = torch.tensor(embeddings_np) + + # Step 3: Load model + print("[INFO] Loading embedding model...") + model_path = Path(__file__).parent / "models" / "mxbai-embed-large-v1" + + # Key: Switch to the absolute path + model_path = model_path.resolve() + + print("[DEBUG] Using absolute model path:", model_path) + + embeddingModel = SentenceTransformer(str(model_path)) + + # Step 4: Questions and perform the RAG retrieval + print("=" * 60) + print(f"[QUERY] {query}") + print("=" * 60) + answer = answerWithRAG(query, embeddings, embeddingModel, docs, docsDict) + + # Step 5: Output results + print("\n[ANSWER CONTEXT]") + print("-" * 60) + print(answer if answer else "No relevant context found.") + print("-" * 60) + + print("[TEST] RAG test completed successfully.") + + +if __name__ == "__main__": + # You can freely modify the query to test different questions + test_rag("Please analyze the data and provide insights on:1. Key patterns in successful vs unsuccessful runs.2. Parameter ranges that appear promising.3. Any timing or wirelength trends.4. Recommendations for subsequent runs.") From 88e027c540108cf6109b81d754195bee8a78ee71 Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:35:26 +0800 Subject: [PATCH 06/42] Create run_all.sh --- flow-Agent/run_all.sh | 22 ++++++++++++++++++++++ 1 file changed, 22 insertions(+) create mode 100644 flow-Agent/run_all.sh diff --git a/flow-Agent/run_all.sh b/flow-Agent/run_all.sh new file mode 100644 index 0000000..371b613 --- /dev/null +++ b/flow-Agent/run_all.sh @@ -0,0 +1,22 @@ +#!/bin/bash +# run_all.sh - sequentially run maindriver.sh for multiple (design, platform) pairs + +# define (design, platform) pairs +pairs=( + "aes asap7" + "aes sky130hd" + "ibex sky130hd" + "ibex asap7" + "jpeg sky130hd" + "jpeg asap7" +) + +# Execute each combination sequentially +for pair in "${pairs[@]}"; do + read d p <<< "$pair" + echo "===========================================" + echo "Running design: $d, platform: $p" + echo "===========================================" + ./maindriver.sh -p "$p" -d "$d" -o DWL + echo +done From 3d6a99a7dcc113fc9481b2c738a302fd7b86d7dc Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:36:31 +0800 Subject: [PATCH 07/42] Add files via upload --- flow-Agent/rag_data | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 flow-Agent/rag_data diff --git a/flow-Agent/rag_data b/flow-Agent/rag_data new file mode 100644 index 0000000..e69de29 From af6bcc7b8935da10c8dccd350c514781a3770309 Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:37:13 +0800 Subject: [PATCH 08/42] Delete flow-Agent/rag_data --- flow-Agent/rag_data | 0 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 flow-Agent/rag_data diff --git a/flow-Agent/rag_data b/flow-Agent/rag_data deleted file mode 100644 index e69de29..0000000 From f74dba4732040474681ca9132485222b12cfc7b9 Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:45:01 +0800 Subject: [PATCH 09/42] Update analyst_agent_workbench.py --- .../analyst_agent_workbench.py | 74 +++++++++++++++++++ 1 file changed, 74 insertions(+) diff --git a/flow-Agent/AutoTuner-integration/ORFS-with-AutoTuner/analyst_agent_workbench.py b/flow-Agent/AutoTuner-integration/ORFS-with-AutoTuner/analyst_agent_workbench.py index 939872c..785e1d5 100644 --- a/flow-Agent/AutoTuner-integration/ORFS-with-AutoTuner/analyst_agent_workbench.py +++ b/flow-Agent/AutoTuner-integration/ORFS-with-AutoTuner/analyst_agent_workbench.py @@ -9,12 +9,47 @@ import anthropic # type: ignore import time # For retry delay import random # For placeholder BayesOpt, can be removed if BayesOpt is robust +from pathlib import Path # For Bayesian Optimization from skopt import Optimizer from skopt.space import Real, Integer, Categorical from skopt.utils import use_named_args # For easier handling of parameters +from rag.index import load_embeddings_and_docs, build_and_save_embeddings +from rag.util import answerWithRAG, modelUtility +from sentence_transformers import SentenceTransformer +import torch + +## ========== New addition: Three QA data paths========== +base_dir = Path(__file__).parent + +# Construct a relative path +qa_paths = [ + base_dir.parent.parent / "EDA-Corpus-main" / "Augmented_Data" / "Question-Answer" / "Flow" / "Flow.csv", + base_dir.parent.parent / "EDA-Corpus-main" / "Augmented_Data" / "Question-Answer" / "General" / "General.csv", + base_dir.parent.parent / "EDA-Corpus-main" / "Augmented_Data" / "Question-Answer" / "Tools" / "Tools.csv", +] +merged_csv_path = "RAGData/RAGFLOWGUIDE.csv" # Unify the file path of the vector library +os.makedirs("RAGData", exist_ok=True) + +def merge_qa_files(file_list, output_path): + dfs = [] + for path in file_list: + if os.path.exists(path): + df = pd.read_csv(path) + # Clean up duplicates and blank lines + df = df.drop_duplicates().dropna(how="any") + dfs.append(df) + print(f"[RAG] Loaded file: {path}, containing {len(df)} records.") + else: + print(f"[Warning] The file does not exist: {path}") + if dfs: + merged = pd.concat(dfs, ignore_index=True) + merged.to_csv(output_path, index=False) + print(f"[RAG] The QA files have been merged into {output_path}, totaling {len(merged)} pieces of data.") + else: + raise FileNotFoundError("[Error] No valid QA files were found.") # --- Global State for Tools --- TOOL_STATE = { "current_df": pd.DataFrame(), @@ -190,6 +225,17 @@ def get_sample_rows(n_rows=3, query_string=None): return header + ":\n" + df_to_sample.sample(actual_n_rows).to_string() except Exception as e: return "Error in get_sample_rows: " + str(e) + "\n" + traceback.format_exc() +def get_rag_context(query, topk=6): + """ + Answer questions using the RAG database. + query: Query strings of users or LLMS + topk: Search for the top k relevant documents + """ + try: + return answerWithRAG(query, embeddings, embeddingModel, docs, docsDict, topk=topk) + except Exception as e: + return f"Error in RAG retrieval: {str(e)}" + def suggest_bayesian_optimization_configs(target_metric_to_minimize, n_suggestions=5, training_data_query=None, validation_data_query=None): log_to_file_and_console("[BAYESOPT] Called suggest_bayesian_optimization_configs.") log_to_file_and_console("[BAYESOPT] Target metric: " + str(target_metric_to_minimize)) @@ -383,6 +429,7 @@ def suggest_bayesian_optimization_configs(target_metric_to_minimize, n_suggestio "get_sample_rows": get_sample_rows, "reset_data_to_all_valid_runs": reset_data_to_all_valid_runs, "suggest_bayesian_optimization_configs": suggest_bayesian_optimization_configs, + "get_rag_context": get_rag_context, "suggest_new_tool": lambda suggested_tool_name, suggested_tool_description: log_to_file_and_console("[LLM TOOL SUGGESTION]\nName: " + str(suggested_tool_name) + "\nDescription: " + str(suggested_tool_description)) or "New tool suggestion noted: " + str(suggested_tool_name) } @@ -506,7 +553,20 @@ def suggest_bayesian_optimization_configs(target_metric_to_minimize, n_suggestio }, "required": ["target_metric_to_minimize"] } + }, + { + "name": "get_rag_context", + "description": "Retrieve the RAG database of OpenROAD-Agent and return relevant API documentation or code snippets for auxiliary analysis.", + "input_schema": { + "type": "object", + "properties": { + "query": {"type": "string", "description": "The question to be queried"}, + "topk": {"type": "integer", "default": 6, "description": "The number of relevant documents returned"} + }, + "required": ["query"] + } } + ] def run_agent_workbench(main_df=None, circuit=None, pdk=None, @@ -551,6 +611,20 @@ def run_agent_workbench(main_df=None, circuit=None, pdk=None, except Exception as e: print("Error initializing Anthropic client: " + str(e)) return + + try: + embeddings_np, docs, docsDict = load_embeddings_and_docs() + embeddings = torch.tensor(embeddings_np) + embeddingModel = SentenceTransformer("mxbai-embed-large-v1") + print("[RAG] The vector database was successfully loaded.") + except FileNotFoundError: + print("[RAG] The vector library does not exist and is under construction...") + merge_qa_files(qa_paths, merged_csv_path) + build_and_save_embeddings(merged_csv_path) + embeddings_np, docs, docsDict = load_embeddings_and_docs() + embeddings = torch.tensor(embeddings_np) + embeddingModel = SentenceTransformer("mxbai-embed-large-v1") + print("[RAG] The vector library has been built and loaded.") session_uuid = uuid.uuid4() context_file_name = log_dir + "/" + args.circuit + "_" + args.pdk + "_" + args.optimization_goal + "_context_" + str(session_uuid) + ".txt" From c7faaa7056b2f9d82528aa2e0227685fc801ff9f Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:46:50 +0800 Subject: [PATCH 10/42] Create README.txt --- flow-Agent/rag_data/README.txt | 1 + 1 file changed, 1 insertion(+) create mode 100644 flow-Agent/rag_data/README.txt diff --git a/flow-Agent/rag_data/README.txt b/flow-Agent/rag_data/README.txt new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/flow-Agent/rag_data/README.txt @@ -0,0 +1 @@ + From e72e61668b8ff847ca235ed4a106935a94d0366c Mon Sep 17 00:00:00 2001 From: yfz2024 Date: Tue, 28 Oct 2025 21:47:47 +0800 Subject: [PATCH 11/42] Add files via upload --- flow-Agent/rag_data/RAGAPIs.csv | 193 ++ flow-Agent/rag_data/RAGCodePiece.csv | 658 +++++ flow-Agent/rag_data/RAGFLOWGUIDE.csv | 4044 ++++++++++++++++++++++++++ flow-Agent/rag_data/docs.pkl | Bin 0 -> 297319 bytes flow-Agent/rag_data/embeddings.npy | Bin 0 -> 2375808 bytes 5 files changed, 4895 insertions(+) create mode 100644 flow-Agent/rag_data/RAGAPIs.csv create mode 100644 flow-Agent/rag_data/RAGCodePiece.csv create mode 100644 flow-Agent/rag_data/RAGFLOWGUIDE.csv create mode 100644 flow-Agent/rag_data/docs.pkl create mode 100644 flow-Agent/rag_data/embeddings.npy diff --git a/flow-Agent/rag_data/RAGAPIs.csv b/flow-Agent/rag_data/RAGAPIs.csv new file mode 100644 index 0000000..0f995a1 --- /dev/null +++ b/flow-Agent/rag_data/RAGAPIs.csv @@ -0,0 +1,193 @@ +Description:,Function Name:,Parameters:,Return Type: +Get the openroad.Tech object,openroad.Tech(),,openroad.Tech +Read .lib files,openroad.Tech.readLiberty(,str(file_name), +Read .lef files,openroad.Tech.readLef(,str(file_name), +Get the openroad db via openroad.Tech object,openroad.Tech.getDB(),,odb.dbDatabase +Get the openroad.Design object,openroad.Design(,openroad.Tech,openroad.Design +Get the I/O pin placer,openroad.Design.getIOPlacer(),,ppl.IOPlacer +Use the name of the layer to get the odb.dbTechLayer object,openroad.Design.getTech().getDB().getTech().findLayer(,str(layer_name),odb.dbTechLayer +Get the parameters of the IO pin placer,ppl.IOPlacer.getParameters(,,ppl.Parameters +Set the minimum distance between each pin of the IO pin placer,ppl.Parameters.setMinDistance(,int(min_dist), +Get the setting of the minimum distance between each pin of the IO pin placer,ppl.Parameters.getMinDistance(),,int +"Set the unit for calling ppl.Parameters.setMinDistance(int) in ""number of tracks"" or in openroad's unit of the IO pin placer",ppl.Parameters.setMinDistanceInTracks(,bool(in_track), +"Check if the unit fot calling ppl.Parameters.setMinDistance(int) of the IO pin placer is in ""number of tracks"" or in openroad's unit, return True if is in ""number of tracks”",ppl.Parameters.getMinDistanceInTracks(),,bool +Get the floorplanner,openroad.Design.getFloorplan(),,ifp.InitFloorplan +"get the minimum placing unit of the design, the input is the name of the site desifned in the technology file",ifp.InitFloorplan.findSite(,str(site),odb.dbSite +"Create tracks, must call this after floorplanning",ifp.InitFloorplan.makeTracks(),, +"Perform floorplanning, utilization is in [0, 100]%. The base_site determines the single-height rows. For hybrid rows it is a site containing a row pattern.",ifp.InitFloorplan.initFloorplan(,"float(utilization), float(aspect_ratio), int(core_space_bottom), int(core_space_top), int(core_space_left), int(core_space_right), odb.dbSite", +"Perform floorplanning, the base_site determines the single-height rows. For hybrid rows it is a site containing a row pattern.",ifp.InitFloorplan.initFloorplan(,"odb.Rect(die), odb.Rect(core), odb.dbSite(base_site)", +Create an openroad.odb.Rect object,odb.Rect(,"int(x1), int(y1), int(x2), int(y2)",odb.Rect +Similar to openroad.get_db_block,openroad.Design.getBlock(),,odb.dbBlock +Get the name of the pin,openroad.Design.getITermName(,odb.dbITerm(),str +Check if a instance is a part of clock nets,openroad.Design.isInClock(,odb.dbInst(),bool +Read the Verilog files into OpenROAD,openroad.Design.readVerilog(,str(file_name), +Read the design file in DEF format (containing placement and routing information),openroad.Design.readDef(,str(file_name), +Find the top module of the Verilog file and connect all other modules. The Verilog files must be read into OpenROAD first.,openroad.Design.link(,str(design_name), +Read the design file written in OpenROAD database format,openroad.Design.readDb(,str(file_name), +Write the design file in OpenROAD database format,openroad.Design.writeDb(,str(file_name), +Change the unit from micron (um) to the unit used in OpenROAD,openroad.Design.micronToDBU(,float(coord),int +Similar to openroad.get_db_tech(),openroad.Design.getTech(),,openroad.Tech +Check is a library cell (master cell) is a buffer,openroad.Design.isBuffer(,odb.dbMaster(),bool +Check if a library cell (master cell) is an inverter,openroad.Design.isInverter(,odb.dbMaster(),bool +Check if a library cell (master cell) is a flip-flop,openroad.Design.isSequential(,odb.dbMaster(),bool +Check if a pin is connected to VDD or VSS net,openroad.Design.isInSupply(,odb.dbITerm(),bool +Get the actual physical wirelength of a routed net,openroad.Design.getNetRoutedLength(,odb.dbNet(),int +"Write DEF file, str is the name of the file",openroad.Design.writeDef(,str(file_name), +Get the openroad.Timing object,openroad.Timing(,openroad.Design,openroad.Timing +Get the sum of switching and internal power of an instance,openroad.Timing.dynamicPower(,"odb.dbInst(), openroad.Timing.getCorners()[int(index)]",float +Get the sum of wire capacitance and pin capacitance of a Net,openroad.Timing.getNetCap(,"odb.dbNet(), openroad.Timing.getCOrners()[int(index)], openroad.Timing.Max",float +Get the sum of wire capacitance and pin capacitance of a Net,openroad.Timing.getNetCap(,"odb.dbNet(), openroad.Timing.getCOrners()[int(index)], openroad.Timing.Min",float +Get the maximum rising arrival time of a pin across all corners,openroad.Timing.getPinArrival(,"odb.dbITerm(), openroad.Timing.Rise, openroad.Timing.Max",float +Get the minimum rising arrival time of a pin across all corners,openroad.Timing.getPinArrival(,"odb.dbITerm(), openroad.Timing.Rise, openroad.Timing.Min",float +Get the maximum falling arrival time of a pin across all corners,openroad.Timing.getPinArrival(,"odb.dbITerm(), openroad.Timing.Fall, openroad.Timing.Max",float +Get the minimum falling arrival time of a pin across all corners,openroad.Timing.getPinArrival(,"odb.dbITerm(), openroad.Timing.Fall, openroad.Timing.Min",float +Get the maximum rising arrival time of a port across all corners,openroad.Timing.getPinArrival(,"odb.dbBTerm(), openroad.Timing.Rise, openroad.Timing.Max",float +Get the minimum rising arrival time of a port across all corners,openroad.Timing.getPinArrival(,"odb.dbBTerm(), openroad.Timing.Rise, openroad.Timing.Min",float +Get the maximum falling arrival time of a port across all corners,openroad.Timing.getPinArrival(,"odb.dbBTerm(), openroad.Timing.Fall, openroad.Timing.Max",float +Get the minimum falling arrival time of a port across all corners,openroad.Timing.getPinArrival(,"odb.dbBTerm(), openroad.Timing.Fall, openroad.Timing.Min",float +Get the maximum rising slack of a pin across all corners ,openroad.Timing.getPinSlack(,"odb.dbITerm(), openroad.Timing.Rise, openroad.Timing.Max",float +Get the minimum rising slack of a pin across all corners ,openroad.Timing.getPinSlack(,"odb.dbITerm(), openroad.Timing.iming.Rise, openroad.Timing.Min",float +Get the maximum falling slack of a pin across all corners ,openroad.Timing.getPinSlack(,"odb.dbITerm(), openroad.Timing.Fall, openroad.Timing.Max",float +Get the minimum falling slack of a pin across all corners ,openroad.Timing.getPinSlack(,"odb.dbITerm(), openroad.Timing.Fall, openroad.Timing.Min",float +Get the maximum rising slack of a port across all corners ,openroad.Timing.getPinSlack(,"odb.dbBTerm(), openroad.Timing.Rise, openroad.Timing.Max",float +Get the minimum rising slack of a port across all corners ,openroad.Timing.getPinSlack(,"odb.dbBTerm(), openroad.Timing.Rise, openroad.Timing.Min",float +Get the maximum falling slack of a port across all corners ,openroad.Timing.getPinSlack(,"odb.dbBTerm(), openroad.Timing.Fall, openroad.Timing.Max",float +Get the minimum falling slack of a port across all corners ,openroad.Timing.getPinSlack(,"odb.dbBTerm(), openroad.Timing.Fall, openroad.Timing.Min",float +Get the minimum slew of the pin across all corners,openroad.Timing.getPinSlew(,"odb.dbITerm, openroad.Timing.Min",float +Get the maximum slew of the pin across all corners,openroad.Timing.getPinSlew(,"odb.dbITerm, openroad.Timing.Max",float +Get the minimum slew of the port across all corners,openroad.Timing.getPinSlew(,"odb.dbBTerm, openroad.Timing.Min",float +Get the maximum slew of the port across all corners,openroad.Timing.getPinSlew(,"odb.dbBTerm, openroad.Timing.Max",float +Get the maximum input capacitance of a pin,openroad.Timing.getPortCap(,"odb.ITerm, openroad.Timing.getCorners()[int(index)], openroad.Timing.Max",float +Get the minimum input capacitance of a pin,openroad.Timing.getPortCap(,"odb.ITerm, openroad.Timing.getCorners()[int(index)], openroad.Timing.Min",float +Check if the pin is the end point of a timing path,openroad.Timing.isEndpoint(,odb.ITerm(),bool +Check if the port is the end point of a timing path,openroad.Timing.isEndpoint(,odb.BTerm(),bool +"Check if the number is ""inf""",openroad.Timing.isTimeInf(,float(time),bool +Get the instance's leakage power,openroad.Timing.staticPower(,"odb.dbInst, openroad.Timing.getCorners()[int(index)]",float +Get the global placer,openroad.Design.getReplace(),,gpl.Replace +"Perform global placement (don't call this function if ""gpl.Replace.doInitialPlace()"" or ""gpl.Replace.doNesterovPlace()"" is called)",gpl.Replace.doIncrementalPlace(,int(thread), +"Perform global placement (don't call this function if ""gpl.Replace.doIncrementalPlace()"" is called)",gpl.Replace.doInitialPlace(),, +"Use ""electrostatic force equations"" to perform global placement (don't call this function if ""gpl.Replace.doIncrementalPlace()"" is called)",gpl.Replace.doNesterovPlace(,int(thread),int +Get the macro placer,openroad.Design.getMacroPlacer(),,mpl.MacroPlacer +"Run macro placement and push all macros to the design boundary, must be called after global placement",mpl.MacroPlacer.placeMacrosCornerMaxWl(),, +"Run macro placement and place all macros together, must be called after global placement",mpl.MacroPlacer.placeMacrosCornerMinWL(),, +Snap the macro to a layer,mpl.MacroPlacer.setSnapLayer(,odb.dbTechLayer, +Set the fence region as a user defined area in microns,mpl.MacroPlacer.setFenceRegion(,"float(lx), doubl(ly), float(ux), float(uy)", +Set the channel width between macros,mpl.MacroPlacer.setChannel(,"float(channel_x), float(channel_y)", +Set the halo around macros,mpl.MacroPlacer.setHalo(,"float(halo_x), float(halo_y)", +Get the openroad db,openroad.get_db(),,odb.dbDatabase +Getting openroad.Tech object via openroad.Design object. Similar to openroad.Design.getTech(),openroad.get_db_tech(),,odb.dbTech +Similar to openroad.Design.getBlock,openroad.get_db_block(),,odb.dbBlock +"Get the detailed placer, or called as legalizer",openroad.Design.getOpendp(),,dpl.Opendp +"Perform legalization, max_displacment is in sites. use zero for defaults.",dpl.Opendp.detailedPlacement(,"int(max_displacement_x), int(max_displacement_y), str(report_file_name), bool(disallow_one_site_gaps)", +Get legalization report,dpl.Opendp.reportLegalizationStats(),, +Check legalization result,dpl.Opendp.checkPlacement(,"bool(verbose), bool(disallow_one_site_gaps), str(report_file_name)", +"Place filler cells after legalization, prefix is the naming pattern of the filler cells",dpl.Opendp.fillerPlacement(,"list(odn.dbMaster), str(prefix)", +Remove filler cells,dpl.Opendp.removeFillers(),, +"Propagate the clock signal, openroad.Design.evalTclString(“create_clock -period 20 [get_ports clk] -name core_clock”) must be celled before this.","openroad.Design.evalTclString(""set_propagated_clock [core_clock]"")",, +Set the unit resistance value and unit capacitance value of the clock net,"openroad.Design.evalTclString(""set_wire_rc -clock -resistance 0.03574 -capacitance 0.07516"")",, +Set the unit resistance value and unit capacitance value of regular signal net,"openroad.Design.evalTclString(""set_wire_rc -signal -resistance 0.03574 -capacitance 0.07516"")",, +Get the module to perform CTS (clock tree synthesis),openroad.Design.getTritonCts(),,cts.TritonCTS +Run CTS (clock tree synthesis),cts.TritonCTS.runTritonCts(,, +Report the CTS result,cts.TritonCTS.reportCtsMetrics(,, +Get the parameter seeting of the CTS module,cts.TritonCTS.getParms(,,cts.CtsOptions +Get the character setting of the CTS module,cts.TritonCTS.getCharacterization(,,cts.TechChar +"Set the clock net by the name, return 0 if complete normally, return 1 if cannot find the clock net with the name",cts.TritonCTS.setClockNets(,str(name), +Set the available clock buffer library cells with he name,cts.TritonCTS.setBufferList(,str(buffers), +Set the rooting clock buffer (starting point) with the name,cts.TritonCTS.setRootBuffer(,str(buffers), +Set the sinking clock buffer (end point) with the name,cts.TritonCTS.setSinkBuffer(,str(buffers), +Set the reference unit for sgmenting the wire,cts.CtsOptions.setWireSegmentUnit(,, +"Get the PDN (power grid, or called power delivery network) generator",openroad.Design.getPdnGen(,,pdn.PdnGen +Get the report of current PDN generation,pdn.PdnGen.report(,, +Get all voltage domain of the design,pdn.PdnGen.getDomains(,,list(pdn.VoltageDomain) +Find the voltage domain with the name of the domain,pdn.PdnGen.findDoamin(,str(name),pdn.VoltageDomain +"Set the voltage domain of the design core, power means the ower net, ground means the ground net",pdn.PdnGen.setCoreDomain(,"odb.dbNet(power), odb.dbNet(switched_power), odb.dbNet(ground), list(odb.dbNet)", +"Build the PDN, if ""trim"" is True, then will clean up some vias and trim the shape of smoe wires. If ""trim"" is set to False, then the PDN will remain the same",pdn.PdnGen.buildGrids(,bool(trim), +Find the high level PDN grid with the name,pdn.PdnGen.findGrid(,str(name), +"Create the high level PDN grid for the macro. ""domain"" is the voltage domain. ""name"" will be the name of this PDN grid. ""starts_with"" can be one of ""pdn.GRID, pdn.POWER, or pdn.GROUND"". ""inst"" is the target macro. ""halo"" is the halo set around the macro. ""pg_pins_to_boundary"" is set to True if the VDD and VSS pins of the macro is set to be around the macro, is is set to False, then VDD and VSS pins will appear within the macro block.",pdn.PdnGen.makeInstanceGrid(,"pdn.VoltageDomain(domain), str(name), pdn.StartsWith(starts_with), odb.dbInst(inst), list(int(halo)), bool(pg_pins_to_boundary), bool(default_grid), list(odb.dbTechLayer(generate_obstructions)), bool(is_bump)", +"Create the PDN ring around the design or the macro. ""grid"" is the high level PDN grid. ""layer0"" and ""layer1"" are the two layers to place the metal stripes of the PDN ring. ""width0"" and ""spacing0"" are the settings of ""layer0"". ""width1"" and ""spacing1"" are the two settings of ""layer1"". ""starts_with"" can be one of ""pdn.GRID, pdn.POWER, or pdn.GROUND"". ""offset"" is the offset setting of the PDN ring. ""pad_offset"" is the offset of padding of the PDN ring. ""extend"" is set to False then the PDN ring will remain the same, if set to True, then it will extend to the boundary. ""pad_pin_layers"" is a list of layers that will connect to pad. ""nets"" can be an empty list.",pdn.PdnGen.makeRing(,"pdn.Grid(grid), odb.dbTechLayer(layer0), int(width0),int(spacing0), odb.dbTechLayer(layer1), int(width1), int(spacing1), pdn.StartsWith(starts_with), list(int(offset)), list(int(pad_offset)), bool(extend), list(odb.dbTechLayer(pad_pin_layers), list(odb.dbNet(nets)", +"Create the PDN stripes at the lowest metal layer and following the pin pattern of the cells. ""extend"" can be either of ""pdn.CORE, pdn.RINGS, pdn.BOUNDARY, or pdn. FIXED"". ""layer"" is the metal layer place the PDN stripes. ""width"" specifies the metal stripe width. ""grid"" is the high level PDN grid.",pdn.PdnGen.makeFollowpin(,"pdn.Grid(grid), odb.dbTechLayer(layer), int(width), pdn.ExtensionMode(extend)", +"Create the PDN stripes generating pattern. ""grid"" is the high level PDN grid. ""layer"" specifies the metal layer. ""starts_with"" can be one of ""pdn.GRID, pdn.POWER, or pdn.GROUND"". ""extend"" can be either of ""pdn.CORE, pdn.RINGS, pdn.BOUNDARY, or pdn. FIXED"". The rest are the settings of the physical dimension of the metal stripes.",pdn.PdnGen.makeStrap(,"pdn.Grid(grid), odb.dbTechLayer(layer), int(width), int(spacing), int(pitch), int(offset), int(number_of_straps), bool(snap), pdn.StartsWith(starts_with), pdn.ExtensionMode(extend), list(odb.dbNet(nets))", +"Connect the stripes between two metal layers (creating vias). ""grid"" is the high level PDN grid. ""layer0"" and ""layer1"" specify the two metal layers. ""cut_pitch_x"" and ""cut_pitch_y"" specify the cut via generating pattern. ""vias"" is a list of vis generating rules defined in the technology file. ""max_rows"" and ""max_columns"" are the settings of the numbers of rows and columns. The key and value of ""dict()"" are odb.dbTechLayer and int. ""dont_use_vias"" is the name of the name of the vis generating rule you do not want to use.",pdn.PdnGen.makeConnect(,"pdn.Grid(grid), odb.dbTechLayer(layer0), odb.dbTechLayer(layer1), int(cut_pitch_x), int(cut_pitch_y), list(odb.dbTechViaGenerateRule(vias)), list(odb.dbTechVia(techvias), int(max_rows), int(max_columns), list(odb.dbTechLayer(ongrid)), dict(), str(dont_use_vias)", +Rip up the selected VDD/VSS net,pdn.PdnGen.ripUp(,(odb.dbNet net), +Check the PDN setup at the end of all pattern are defined,pdn.PdnGen.checkSetup(,, +"Write the PDN generation result to OpenROAD database. Usually set ""add_pins"" to True. ""report_file"" specifies the name of the report file.",pdn.PdnGen.writeToDb(,"bool(add_pins), str(report_file)", +Get the PDN analysis tool,openroad.Design.getPDNSim(),, +Specifies the target VDD/VSS net,psm.PDNSim.setNet(,odb.dbNet(net), +"Analyze the PDN, if set all files to enpty strings and set ""enable_em"" to False, PDNSim will use the default setting.",psm.PDNSim.analyzePowerGrid(,"str(voltage_file), bool(enable_em), str(em_file), str(error_file)", +"Perform IR drop analysis, ""layer"" specifies the layer.",psm.PDNSim.getIRDropForLayer(,odb.dbTechLayer(layer), +Set the corner information for the PDN analysis tool.,"openroad.Design.evalTclString(f""psm::set_corner [sta::cmd_corner]"")",, +Get the global router.,openroad.Design.getGlobalRouter(),,grt.GlobalRouter +Set the lowest routing layer,grt.GlobalRouter.setMinRoutingLayer(,int(min_layer), +Set the highest routing layer,grt.GlobalRouter.setMaxRoutingLayer(,int(max_layer), +Set the lowest routing layer for clock net,grt.GlobalRouter.setMinLayerForClock(,int(min_layer), +Set the highest routing layer for clock net,grt.GlobalRouter.setMaxLayerForClock(,int(max_layer), +Set the iteration to run if facing overflow in some gcells,grt.GlobalRouter.setOverflowIterations(,int(iterations), +"Run global routing, all default values are False.",grt.GlobalRouter.globalRoute(,"bool(save_guides), bool(start_incremental), bool(end_incremental)", +Get the detailed router,openroad.Design.getTritonRoute(),,drt.TritonRoute +Run detailed routing.,drt.TritonRoute.main(),, +Get the amount of DRVs,drt.getNumDRVs(),,int +Get the parameter settings of the detailed router.,drt.ParamStruct(),,drt.ParamStruct +Number of iteraion of detailed routing. Assign an integer to this variable,drt.ParamStruct.drouteEndIter(),, +Assign boolean to this variable to enable via generating during detailed routing,drt.ParamStruct.enableViaGen(),, +Find the instance using the name of that instance,odb.dbBlock.findInst(,str(name),odb.dbInst +Get a list of all nets,odb.dbBlock.getNets(),,list(odb.dbNet) +Get a list of all I/O ports,odb.dbBlock.getBTerms(),,list(odb.dbBTerm) +Find the I/O port using the name of that I/O port,odb.dbBlock.findBTerm(,str(name),odb.dbBTerm +Get a list of all pins,odb.dbBlock.getITerms(),,list(odb.dbITerm) +Find the pin using the name of that pin,odb.dbBlock.findITerm(,str(name),odb.dbITerm +Get a list of all instances,odb.dbBlock.getInsts(),,list(odb.dbInst) +Get db unit per micron (um),odb.dbBlock.getDbUnitsPerMicron(),,int +Get the core rectangle,odb.dbBlock.getCoreArea(),,odb.Rect +Get a list of all rows in the design,odb.dbBlock.getRows(),,list(odb.dbRow) +Get the site used in this row,odb.dbRow.getSite(),,odb.dbSite +Get the bottom left x location of this rectangle,odb.Rect.xMin(),,int +Get the bottom left y location of this rectangle,odb.Rect.yMin(),,int +Get the top right x location of this rectangle,odb.Rect.xMax(),,int +Get the top right y location of this rectangle,odb.Rect.yMax(),,int +Connect pins with nets. odb.dbBlock.addGlobalConnect should be executed before calling this function,odb.dbBlock.globalConnect(),, +"Given the pattern of the instance names, connect the net to the pins of instances that match the pin pattern",odb.dbBlock.addGlobalConnect(,"odb.dbRegion(region), str(instPattern), str(pinPattern), odb.dbNet(net), bool(do_connect)", +Getting openroad.Tech object via openroad.odb.dbBlock object. Similar to openroad.Design.getTech(),odb.dbBlock.getTech(),,odb.dbTech +"Return True if the net is marked as selected, return False if the net is not marked as selected.",odb.dbNet.isSelect(),,bool +Get the name of the net,odb.dbNet.getName(),,str +"Set the wire type of the net. Input can only be one of the followings: (""NONE"", ""COVER"", ""FIXED"", ""ROUTED"", ""SHIELD"", “NOSHIELD"")",odb.dbNet.setWireType(,str, +"Get the odb.dbWireType object in string. Return value can be one of the followings: (""NONE"", ""COVER"", ""FIXED"", ""ROUTED"", ""SHIELD"", ""NOSHIELD"")",odb.dbNet.getWireType(,,str +Get the total coupling capacitance of the net,odb.dbNet.getTotalCouplingCap(),,float +Get the total capacitance of the net,odb.dbNet.getTotalCapacitance(),,float +Get the total resistance of the net,odb.dbNet.getTotalResistance(),,float +Get all pins of the net,odb.dbNet.getITerms(),,list(odb.dbITerm) +Get all pins of the instance,odb.dbInst.getITerms(),,list(odb.dbITerm) +Get the name of the instance,odb.dbInst.getName(),,str +Get the x y location as a odb.Point object of the instance. Similar to odb.dbInst.getLocation(),odb.dbInst.getOrigin(),,odb.Point +Get the x location of the odb.Point object,odb.Point.getX(),,int +Get the y location of the odb.Point object,odb.Point.getY(),,int +Set the x y location of the instance. Similar to odb.dbInst.setLocation(),odb.dbInst.setOrigin(,"int(x), int(y)", +Get the x and y location as a odb.Point object of the instance. Similar to odb.dbInst.getOrigin(),odb.dbInst.getLocation(),,odb.Point +Set the x and y location of the instance. Similar to odb.dbInst.setOrigin(),odb.dbInst.setLocation(,"int(x), int(y)", +"Get the placement status of the instance. Status can only be one of the followings: (""NONE"", ""UNPLACED"", ""SUGGESTED"", ""PLACED"", ""LOCKED"", ""FIRM"", “COVER"")",odb.dbInst.getPlacementStatus(),,str +"Set the placement status of the instance. Status can only be one of the followings: (""NONE"", ""UNPLACED"", ""SUGGESTED"", ""PLACED"", ""LOCKED"", ""FIRM"", “COVER"")",odb.dbInst.setPlacementStatus(,str, +"Get the rotation (orientation) as a string of the instance. Orient can only be one of the followings: (""R0"", ""R90"", ""R180"", ""R270"", ""MY"", ""MYR90"", ""MX"", “MXR90"")",odb.dbInst.getOrient(),,str +"Set the rotation (orientation) of the instance. Orient can only be one of the followings: (""R0"", ""R90"", ""R180"", ""R270"", ""MY"", ""MYR90"", ""MX"", “MXR90"")",odb.dbInst.setOrient(,str, +Get the dbTransform object of the instance.,odb.dbInst.getTransform(),,odb.dbTransform +Set the dbTransform object of the instance.,odb.dbInst.setTransform(,odb.dbTransform(transform), +"Get the orientation (rotation) of the transform object, odb.dbInst.getTransform() function must be called before calling this function.",odb.dbTransform.getOrient(),,odb.dbOrientType +"Get the x and y location of the transform object, odb.dbInst.getTransform() function must be called before calling this function.",odb.dbTransform.getOffset(),,odb.Point +"Update the orientation (rotation) of the transform object, odb.dbInst.getTransform() function must be called before calling this function.",odb.dbTransform.setOrient(,str, +"Update the x and y location of the transform object, odb.dbInst.getTransform() function must be called before calling this function.",odb.dbTransform.setOffset(,odb.Point(point), +"Update the x and y location and the orientation (rotation) of the transform object, odb.dbInst.getTransform() function must be called before calling this function.",odb.dbTransform.setTransform(,"str, odb.Point", +Invert the x and y location and the rotation (orientation) of the transform,odb.dbTransform.invert(),, +Set the x and y location of the point object,odb.Point(,"int(x), int(y)",odb.Point +"v=True to set the instance as a ""do not touch” or “don’t touch” type instance. Use v=False to reset the ""do not touch"" setting.",odb.dbInst.setDoNotTouch(,bool(v), +"Return True if the instance is set as ""do not touch"" instance, return False if the instance is not set as ""do not touch"" instance",odb.dbInst.isDoNotTouch(),,bool +Return True if the instance is placed.,odb.dbInst.isPlaced(),,bool +Get the net connected to this pin,odb.dbITerm.getNet(),,odb.dbNet +Return True if the pin is an output pin of the instance. Return False if the pin is not an output pin of the instance.,odb.dbITerm.isOutputSignal(),,bool +Return True if the pin is an input pin of the instance. Return False if the pin is not an input pin of the instance.,odb.dbITerm.isInputSignal(),,bool +"Get the signal type of the net. Return ""POWER"" if the net is a power (VDD) net. Return ""GROUND"" is the net is a ground (VSS) net.",odb.dbNet.getSigType(),,str +"Set the signal type of the net. Set type to ""POWER"" if the net is a power (VDD) net. Set type to ""GROUND"" is the net is a ground (VSS) net.",odb.dbNet.setSigType(,str(type), +Get the cut layer class rule of the technology layer,odb.dbTechLayer.getTechLayerCutClassRules(,,list(odb.dbTechLayerCutClassRule) +Upsize or downsize the instance with the input “master” library cell,odb.dbInst.swapMaster(,odb.dbMaster(master), +Use name to find the master cell (library cell). Return None if the name does not match any master cell.,odb.dbDatabase.findMaster(,str(name),odb.dbMaster +Create a clock signal at the clk_i port with a period of 50 ps and name it core_clk.,openroad.Design.evalTclString(“create_clock -period 50 [get_ports clk_i] -name core_clock”),, +"Return True if the net’s disconnected flag is set to True, which typically means the net is disconnected from all pins. Return False if the flag is set to False, indicating that the net has connections with pins.",odb.dbNet.isDisconnected(),,Bool +Print opcodes and data of its wire,odb.dbNet.printWire(),, +"Return True if the master is a filler cell, return False if the master is not a filler cell.",odb.dbMaster.isFiller(),,bool \ No newline at end of file diff --git a/flow-Agent/rag_data/RAGCodePiece.csv b/flow-Agent/rag_data/RAGCodePiece.csv new file mode 100644 index 0000000..fa454ad --- /dev/null +++ b/flow-Agent/rag_data/RAGCodePiece.csv @@ -0,0 +1,658 @@ +Description:,Code Piece: +Template of reading .lib (liberty) files,"from openroad import Tech +from pathlib import Path + +# Initialize OpenROAD objects and read technology files +tech = Tech() +# Set paths to library and design files +libDir = Path(""../Design/nangate45/lib"") + +# Read all liberty file from the library directories +libFiles = libDir.glob(""*.lib"") + +# Load liberty timing libraries +for libFile in libFiles: + tech.readLiberty(libFile.as_posix())" +Template of reading .lef files,"from openroad import Tech +from pathlib import Path + +# Initialize OpenROAD objects and read technology files +tech = Tech() +# Set paths to library and design files +lefDir = Path(""../Design/nangate45/lef"") +techlefDir = Path(""../Design/nangate45/lef"") + +# Read all LEF files from the library directories +techLefFiles = lefDir.glob(""*.tech.lef"") +lefFiles = lefDir.glob('*.lef') + +# Load technology and cell LEF files +for techLefFile in techLefFiles: + tech.readLef(techLefFile.as_posix()) +for lefFile in lefFiles: + tech.readLef(lefFile.as_posix())" +Template of reading technology files,"from openroad import Tech +from pathlib import Path + +# Initialize OpenROAD objects and read technology files +tech = Tech() +# Set paths to library and design files +techlefDir = Path(""../Design/nangate45/lef"") + +# Read all tech led files from the library directories +techLefFiles = lefDir.glob(""*.tech.lef"") + +# Load technology and cell LEF files +for techLefFile in techLefFiles: + tech.readLef(techLefFile.as_posix())" +Template of reading verilog files (reading netlist file),"from openroad import Tech, Design +from pathlib import Path + +# Initialize OpenROAD objects and read technology files +tech = Tech() +# Set paths to library and design files +libDir = Path(""../Design/nangate45/lib"") +lefDir = Path(""../Design/nangate45/lef"") +techlefDir = Path(""../Design/nangate45/lef"") +designDir = Path(""../Design/"") + +design_name = ""1_synth"" +design_top_module_name = ""gcd"" + +# Read all liberty (.lib) and LEF files from the library directories +libFiles = libDir.glob(""*.lib"") +techLefFiles = lefDir.glob(""*.tech.lef"") +lefFiles = lefDir.glob('*.lef') + +# Load liberty timing libraries +for libFile in libFiles: + tech.readLiberty(libFile.as_posix()) +# Load technology and cell LEF files +for techLefFile in techLefFiles: + tech.readLef(techLefFile.as_posix()) +for lefFile in lefFiles: + tech.readLef(lefFile.as_posix()) + +# Create design and read Verilog netlist +design = Design(tech) +verilogFile = designDir/str(design_name + "".v"") +design.readVerilog(verilogFile.as_posix()) +design.link(design_top_module_name)" +Template of reading OpenROAD design file in .odb format,"from openroad import Tech, Design + +# Initialize OpenROAD objects and read technology files +tech = Tech() +# Set paths to library and design files +libDir = Path(""../Design/nangate45/lib"") +lefDir = Path(""../Design/nangate45/lef"") +techlefDir = Path(""../Design/nangate45/lef"") +designDir = Path(""../Design/"") + +design_name = ""1_synth"" +design_top_module_name = ""gcd"" + +# Read all liberty (.lib) and LEF files from the library directories +libFiles = libDir.glob(""*.lib"") +techLefFiles = lefDir.glob(""*.tech.lef"") +lefFiles = lefDir.glob('*.lef') + +# Load liberty timing libraries +for libFile in libFiles: + tech.readLiberty(libFile.as_posix()) +# Load technology and cell LEF files +for techLefFile in techLefFiles: + tech.readLef(techLefFile.as_posix()) +for lefFile in lefFiles: + tech.readLef(lefFile.as_posix()) + +# Create design and read ode file +design = Design(tech) +odbFile = designDir/str(design_name + "".odb"") +design.readDb(odbFile.as_posix())" +Template of reading DEF (.def) files,"from openroad import Tech, Design + +# Initialize OpenROAD objects and read technology files +tech = Tech() +# Set paths to library and design files +libDir = Path(""../Design/nangate45/lib"") +lefDir = Path(""../Design/nangate45/lef"") +techlefDir = Path(""../Design/nangate45/lef"") +designDir = Path(""../Design/"") + +design_name = ""1_synth"" +design_top_module_name = ""gcd"" + +# Read all liberty (.lib) and LEF files from the library directories +libFiles = libDir.glob(""*.lib"") +techLefFiles = lefDir.glob(""*.tech.lef"") +lefFiles = lefDir.glob('*.lef') + +# Load liberty timing libraries +for libFile in libFiles: + tech.readLiberty(libFile.as_posix()) +# Load technology and cell LEF files +for techLefFile in techLefFiles: + tech.readLef(techLefFile.as_posix()) +for lefFile in lefFiles: + tech.readLef(lefFile.as_posix()) + +# Create design and read def file +design = Design(tech) +defFile = designDir/str(design_name + "".def"") +design.readDef(defFile.as_posix())" +Template of creating and propagate the clock signal,"clock_period = 200 +port_name = ""port_name"" +clock_name = ""clock_name"" +# Create clock signal +design.evalTclString(""create_clock -period %s [get_ports %s] -name %s""%(clock_period, port_name, clock_name)) +# Propagate the clock signal +design.evalTclString(""set_propagated_clock [all_clocks]"")" +Template of running floorplanning with utilization rate (hight/width),"# Initialize floorplan with core and die area +floorplan = design.getFloorplan() +# Set die area to 60um x 50um +# Initialize floorplan with FreePDK45 site +site = floorplan.findSite(""FreePDK45_38x28_10R_NP_162NW_34O"") +utilization = 0.5 +aspect_ratio = 1.0 +leftSpace = design.micronToDBU(10) +rightSpace = design.micronToDBU(10) +topSpace = design.micronToDBU(10) +bottomSpace = design.micronToDBU(10) +floorplan.initFloorplan(utilization, aspect_ratio, bottomSpace, topSpace, leftSpace, rightSpace, site) +floorplan.makeTracks()" +Template of running floorplanning with specific die and core area,"import odb +# Initialize floorplan with core and die area +floorplan = design.getFloorplan() +# Set die area to 60um x 50um +die_area = odb.Rect(design.micronToDBU(0), design.micronToDBU(0), + design.micronToDBU(60), design.micronToDBU(50)) +# Set core area to 50um x 40um with 5um margins +core_area = odb.Rect(design.micronToDBU(5), design.micronToDBU(5), + design.micronToDBU(55), design.micronToDBU(45)) +# Initialize floorplan with FreePDK45 site +site = floorplan.findSite(""FreePDK45_38x28_10R_NP_162NW_34O"") +floorplan.initFloorplan(die_area, core_area, site) +floorplan.makeTracks()" +Template of placing I/O pins (ports),"# Configure and run I/O pin placement +params = design.getIOPlacer().getParameters() +params.setRandSeed(42) +params.setMinDistanceInTracks(False) +params.setMinDistance(design.micronToDBU(0)) +params.setCornerAvoidance(design.micronToDBU(0)) +# Place I/O pins on metal8 (horizontal) and metal9 (vertical) layers +design.getIOPlacer().addHorLayer(design.getTech().getDB().getTech().findLayer(""metal8"")) +design.getIOPlacer().addVerLayer(design.getTech().getDB().getTech().findLayer(""metal9"")) +IOPlacer_random_mode = True +design.getIOPlacer().runAnnealing(IOPlacer_random_mode)" +Template of running global placement,"# Configure and run global placement +gpl = design.getReplace() +gpl.setTimingDrivenMode(False) +gpl.setRoutabilityDrivenMode(True) +gpl.setUniformTargetDensityMode(True) +# Limit initial placement iterations and set density penalty +gpl.setInitialPlaceMaxIter(10) +gpl.setInitDensityPenalityFactor(0.05) +gpl.doInitialPlace(threads = 4) +gpl.doNesterovPlace(threads = 4) +gpl.reset()" +Template of running macro placer,"# Place macro blocks if present +macros = [inst for inst in design.getBlock().getInsts() if inst.getMaster().isBlock()] +if len(macros) > 0: + mpl = design.getMacroPlacer() + block = design.getBlock() + core = block.getCoreArea() + mpl.place( + num_threads = 64, + max_num_macro = len(macros)//8, + min_num_macro = 0, + max_num_inst = 0, + min_num_inst = 0, + tolerance = 0.1, + max_num_level = 2, + coarsening_ratio = 10.0, + large_net_threshold = 50, + signature_net_threshold = 50, + halo_width = 2.0, + halo_height = 2.0, + fence_lx = block.dbuToMicrons(core.xMin()), + fence_ly = block.dbuToMicrons(core.yMin()), + fence_ux = block.dbuToMicrons(core.xMax()), + fence_uy = block.dbuToMicrons(core.yMax()), + area_weight = 0.1, + outline_weight = 100.0, + wirelength_weight = 100.0, + guidance_weight = 10.0, + fence_weight = 10.0, + boundary_weight = 50.0, + notch_weight = 10.0, + macro_blockage_weight = 10.0, + pin_access_th = 0.0, + target_util = 0.25, + target_dead_space = 0.05, + min_ar = 0.33, + snap_layer = 4, + bus_planning_flag = False, + report_directory = """" + )" +Template of running detailed placement,"# Run initial detailed placement +site = design.getBlock().getRows()[0].getSite() +# Allow 1um x-displacement and 3um y-displacement +max_disp_x = int(design.micronToDBU(1)) +max_disp_y = int(design.micronToDBU(3)) +# Remove filler cells to be able to move the cells +design.getOpendp().removeFillers() +design.getOpendp().detailedPlacement(max_disp_x, max_disp_y, """", False)" +Template of running CTS (clock tree synthesis),"# Configure and run clock tree synthesis +design.evalTclString(""set_propagated_clock [get_clocks {core_clock}]"") +# Set RC values for clock and signal nets +design.evalTclString(""set_wire_rc -clock -resistance 0.03574 -capacitance 0.07516"") +design.evalTclString(""set_wire_rc -signal -resistance 0.03574 -capacitance 0.07516"") +cts = design.getTritonCts() +parms = cts.getParms() +parms.setWireSegmentUnit(20) +# Configure clock buffers +cts.setBufferList(""BUF_X2"") +cts.setRootBuffer(""BUF_X2"") +cts.setSinkBuffer(""BUF_X2"") +cts.runTritonCts() + +# Run final detailed placement +site = design.getBlock().getRows()[0].getSite() +max_disp_x = int(design.micronToDBU(1) / site.getWidth()) +max_disp_y = int(design.micronToDBU(3) / site.getHeight()) +design.getOpendp().detailedPlacement(max_disp_x, max_disp_y, """", False)" +Template of placing filler cells,"import openroad as ord +# Insert filler cells +db = ord.get_db() +filler_masters = list() +# filler cells' naming convention +filler_cells_prefix = ""FILLCELL_"" +for lib in db.getLibs(): + for master in lib.getMasters(): + if master.getType() == ""CORE_SPACER"": + filler_masters.append(master) +if len(filler_masters) == 0: + print(""no filler cells in library!"") +else: + design.getOpendp().fillerPlacement(filler_masters = filler_masters, + prefix = filler_cells_prefix, + verbose = False)" +Template of performing power planning (creating power delivery network (PDN)) with power rings,"import pdn, odb +# Configure power delivery network +# Set up global power/ground connections +for net in design.getBlock().getNets(): + if net.getSigType() == ""POWER"" or net.getSigType() == ""GROUND"": + net.setSpecial() +VDD_net = design.getBlock().findNet(""VDD"") +VSS_net = design.getBlock().findNet(""VSS"") +switched_power = None +secondary = list() +# Create VDD/VSS nets if they don't exist +if VDD_net == None: + VDD_net = odb.dbNet_create(design.getBlock(), ""VDD"") + VDD_net.setSpecial() + VDD_net.setSigType(""POWER"") +if VSS_net == None: + VSS_net = odb.dbNet_create(design.getBlock(), ""VSS"") + VSS_net.setSpecial() + VSS_net.setSigType(""GROUND"") + +# Connect power pins to global nets +design.getBlock().addGlobalConnect(region = None, + instPattern = "".*"", + pinPattern = ""^VDD$"", + net = VDD_net, + do_connect = True) +design.getBlock().addGlobalConnect(region = None, + instPattern = "".*"", + pinPattern = ""^VDDPE$"", + net = VDD_net, + do_connect = True) +design.getBlock().addGlobalConnect(region = None, + instPattern = "".*"", + pinPattern = ""^VDDCE$"", + net = VDD_net, + do_connect = True) +design.getBlock().addGlobalConnect(region = None, + instPattern = "".*"", + pinPattern = ""^VSS$"", + net = VSS_net, + do_connect = True) +design.getBlock().addGlobalConnect(region = None, + instPattern = "".*"", + pinPattern = ""^VSSE$"", + net = VSS_net, + do_connect = True) +design.getBlock().globalConnect() + +# Configure power domains +pdngen = design.getPdnGen() +pdngen.setCoreDomain(power = VDD_net, + switched_power = switched_power, + ground = VSS_net, + secondary = secondary) + +# Configure power ring dimensions +core_ring_width = [design.micronToDBU(2), design.micronToDBU(2)] +core_ring_spacing = [design.micronToDBU(2), design.micronToDBU(2)] +core_ring_core_offset = [design.micronToDBU(0) for i in range(4)] +core_ring_pad_offset = [design.micronToDBU(0) for i in range(4)] +pdn_cut_pitch = [design.micronToDBU(0) for i in range(2)] + +# Get routing layers for power ring connections +ring_connect_to_pad_layers = list() +for layer in design.getTech().getDB().getTech().getLayers(): + if layer.getType() == ""ROUTING"": + ring_connect_to_pad_layers.append(layer) + +# Create power grid for standard cells +domains = [pdngen.findDomain(""Core"")] +halo = [design.micronToDBU(0) for i in range(4)] +for domain in domains: + pdngen.makeCoreGrid(domain = domain, + name = ""top"", + starts_with = pdn.GROUND, + pin_layers = [], + generate_obstructions = [], + powercell = None, + powercontrol = None, + powercontrolnetwork = ""STAR"") + +# Get metal layers for power grid +m1 = design.getTech().getDB().getTech().findLayer(""metal1"") +m4 = design.getTech().getDB().getTech().findLayer(""metal4"") +m7 = design.getTech().getDB().getTech().findLayer(""metal7"") +m8 = design.getTech().getDB().getTech().findLayer(""metal8"") + +grid = pdngen.findGrid(""top"") +for g in grid: + # Create power rings around core area + pdngen.makeRing(grid = g, + layer0 = m7, + width0 = core_ring_width[0], + spacing0 = core_ring_spacing[0], + layer1 = m8, + width1 = core_ring_width[0], + spacing1 = core_ring_spacing[0], + starts_with = pdn.GRID, + offset = core_ring_core_offset, + pad_offset = core_ring_pad_offset, + extend = False, + pad_pin_layers = ring_connect_to_pad_layers, + nets = [], + allow_out_of_die = True) + + # Create horizontal power straps on metal1 for standard cell connections + pdngen.makeFollowpin(grid = g, + layer = m1, + width = design.micronToDBU(0.07), + extend = pdn.CORE) + + # Create vertical power straps on metal4 and metal7 + pdngen.makeStrap(grid = g, + layer = m4, + width = design.micronToDBU(1.2), + spacing = design.micronToDBU(1.2), + pitch = design.micronToDBU(6), + offset = design.micronToDBU(0), + number_of_straps = 0, + snap = False, + starts_with = pdn.GRID, + extend = pdn.CORE, + nets = []) + pdngen.makeStrap(grid = g, + layer = m7, + width = design.micronToDBU(1.4), + spacing = design.micronToDBU(1.4), + pitch = design.micronToDBU(10.8), + offset = design.micronToDBU(0), + number_of_straps = 0, + snap = False, + starts_with = pdn.GRID, + extend = pdn.RINGS, + nets = []) + pdngen.makeStrap(grid = g, + layer = m8, + width = design.micronToDBU(1.4), + spacing = design.micronToDBU(1.4), + pitch = design.micronToDBU(10.8), + offset = design.micronToDBU(0), + number_of_straps = 0, + snap = False, + starts_with = pdn.GRID, + extend = pdn.BOUNDARY, + nets = []) + + # Create via connections between power grid layers + pdngen.makeConnect(grid = g, + layer0 = m1, + layer1 = m4, + cut_pitch_x = pdn_cut_pitch[0], + cut_pitch_y = pdn_cut_pitch[1], + vias = [], + techvias = [], + max_rows = 0, + max_columns = 0, + ongrid = [], + split_cuts = dict(), + dont_use_vias = """") + pdngen.makeConnect(grid = g, + layer0 = m4, + layer1 = m7, + cut_pitch_x = pdn_cut_pitch[0], + cut_pitch_y = pdn_cut_pitch[1], + vias = [], + techvias = [], + max_rows = 0, + max_columns = 0, + ongrid = [], + split_cuts = dict(), + dont_use_vias = """") + pdngen.makeConnect(grid = g, + layer0 = m7, + layer1 = m8, + cut_pitch_x = pdn_cut_pitch[0], + cut_pitch_y = pdn_cut_pitch[1], + vias = [], + techvias = [], + max_rows = 0, + max_columns = 0, + ongrid = [], + split_cuts = dict(), + dont_use_vias = """") + +# Verify and build power grid +pdngen.checkSetup() +pdngen.buildGrids(False) +pdngen.writeToDb(True, ) +pdngen.resetShapes()" +Template of creating power distribute networks (PDN) for macros,"import pdn +pdngen = design.getPdnGen() +domains = [pdngen.findDomain(""Core"")] +# Create power grid for macro blocks +macros = [inst for inst in design.getBlock().getInsts() if inst.getMaster().isBlock()] +m5 = design.getTech().getDB().getTech().findLayer(""metal5"") +m6 = design.getTech().getDB().getTech().findLayer(""metal6"") +for i in range(len(macros)): + # Create power grid for each macro + for domain in domains: + pdngen.makeInstanceGrid(domain = domain, + name = ""CORE_macro_grid_"" + str(i), + starts_with = pdn.GROUND, + inst = macros[i], + halo = halo, + pg_pins_to_boundary = True, + default_grid = False, + generate_obstructions = [], + is_bump = False) + grid = pdngen.findGrid(""CORE_macro_grid_"" + str(i)) + for g in grid: + # Create power straps on metal5 and metal6 for macro connections + pdngen.makeStrap(grid = g, + layer = m5, + width = design.micronToDBU(1.2), + spacing = design.micronToDBU(1.2), + pitch = design.micronToDBU(6), + offset = design.micronToDBU(0), + number_of_straps = 0, + snap = True, + starts_with = pdn.GRID, + extend = pdn.CORE, + nets = []) + pdngen.makeStrap(grid = g, + layer = m6, + width = design.micronToDBU(1.2), + spacing = design.micronToDBU(1.2), + pitch = design.micronToDBU(6), + offset = design.micronToDBU(0), + number_of_straps = 0, + snap = True, + starts_with = pdn.GRID, + extend = pdn.CORE, + nets = []) + + # Create via connections between macro power grid layers + pdngen.makeConnect(grid = g, + layer0 = m4, + layer1 = m5, + cut_pitch_x = pdn_cut_pitch[0], + cut_pitch_y = pdn_cut_pitch[1], + vias = [], + techvias = [], + max_rows = 0, + max_columns = 0, + ongrid = [], + split_cuts = dict(), + dont_use_vias = """") + pdngen.makeConnect(grid = g, + layer0 = m5, + layer1 = m6, + cut_pitch_x = pdn_cut_pitch[0], + cut_pitch_y = pdn_cut_pitch[1], + vias = [], + techvias = [], + max_rows = 0, + max_columns = 0, + ongrid = [], + split_cuts = dict(), + dont_use_vias = """") + pdngen.makeConnect(grid = g, + layer0 = m6, + layer1 = m7, + cut_pitch_x = pdn_cut_pitch[0], + cut_pitch_y = pdn_cut_pitch[1], + vias = [], + techvias = [], + max_rows = 0, + max_columns = 0, + ongrid = [], + split_cuts = dict(), + dont_use_vias = """") + +# Verify and build power grid +pdngen.checkSetup() +pdngen.buildGrids(False) +pdngen.writeToDb(True, ) +pdngen.resetShapes()" +Template of performing IR (voltage) drop analysis for nodes on metal 1 grids,"import psm + +# Run static IR drop analysis +psm_obj = design.getPDNSim() +timing = Timing(design) +source_types = [psm.GeneratedSourceType_FULL, + psm.GeneratedSourceType_STRAPS, + psm.GeneratedSourceType_BUMPS] +# Analyze VDD power grid IR drop +psm_obj.analyzePowerGrid(net = design.getBlock().findNet(""VDD""), + enable_em = False, corner = timing.getCorners()[0], + use_prev_solution = False, + em_file = """", + error_file = """", + voltage_source_file = """", + voltage_file = """", + source_type = source_types[2])" +"Template of reporting internal power, switching power, and leakage power","# Report Power +design.evalTclString(""report_power"")" +Template of performing global routing,"# Configure and run global routing +# Set routing layer ranges for signal and clock nets +signal_low_layer = design.getTech().getDB().getTech().findLayer(""metal1"").getRoutingLevel() +signal_high_layer = design.getTech().getDB().getTech().findLayer(""metal7"").getRoutingLevel() +clk_low_layer = design.getTech().getDB().getTech().findLayer(""metal1"").getRoutingLevel() +clk_high_layer = design.getTech().getDB().getTech().findLayer(""metal7"").getRoutingLevel() + +grt = design.getGlobalRouter() +grt.setMinRoutingLayer(signal_low_layer) +grt.setMaxRoutingLayer(signal_high_layer) +grt.setMinLayerForClock(clk_low_layer) +grt.setMaxLayerForClock(clk_high_layer) +grt.setAdjustment(0.5) +grt.setVerbose(True) +grt.globalRoute(True)" +Template of performing detailed routing,"import drt + +# Configure and run detailed routing +drter = design.getTritonRoute() +params = drt.ParamStruct() +params.outputMazeFile = """" +params.outputDrcFile = """" +params.outputCmapFile = """" +params.outputGuideCoverageFile = """" +params.dbProcessNode = """" +params.enableViaGen = True +params.drouteEndIter = 1 +params.viaInPinBottomLayer = """" +params.viaInPinTopLayer = """" +params.orSeed = -1 +params.orK = 0 +params.bottomRoutingLayer = ""metal1"" +params.topRoutingLayer = ""metal7"" +params.verbose = 1 +params.cleanPatches = True +params.doPa = True +params.singleStepDR = False +params.minAccessPoints = 1 +params.saveGuideUpdates = False +drter.setParams(params) +drter.main()" +Template function to horizontally flip the instance,"# This function is not provided by OpenROAD, you have to create this function. +def flipX(value): + if value == ""R0"": + return ""MX"" + elif value == ""R90"": + return ""MYR90"" + elif value == ""R180"": + return ""MY"" + elif value == ""R270"": + return ""MXR90"" + elif value == ""MY"": + return ""R180"" + elif value == ""MYR90"": + return ""R90"" + elif value == ""MX"": + return ""R0"" + elif value == ""MXR90"": + return ""R270""" +Template function to vertically flip the instance,"# This function is not provided by OpenROAD, you have to create this function. +def flipY(value): + if value == ""R0"": + return ""MY"" + elif value == ""R90"": + return ""MXR90"" + elif value == ""R180"": + return ""MX"" + elif value == ""R270"": + return ""MYR90"" + elif value == ""MY"": + return ""R0"" + elif value == ""MYR90"": + return ""R270"" + elif value == ""MX"": + return ""R180"" + elif value == ""MXR90"": + return ""R90""" +Template of getting the library cell (master cell) from the OpenROAD db,"# Get the database +db = ord.get_db() +# Define the new library cell name +new_mast_name = 'NOR_2X6' +# Check if the required library cell exists in the database +new_mast = db.findMaster(new_mast_name)" \ No newline at end of file diff --git a/flow-Agent/rag_data/RAGFLOWGUIDE.csv b/flow-Agent/rag_data/RAGFLOWGUIDE.csv new file mode 100644 index 0000000..d498d5b --- /dev/null +++ b/flow-Agent/rag_data/RAGFLOWGUIDE.csv @@ -0,0 +1,4044 @@ +FlowStage,ErrorMessage,LikelyCause,RecommendedFix,ExampleWrongCode +FILE,"[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) r",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) r",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) r",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) r",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'exportDef'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +TypeError: Design.writeDb() got an unexpected keyword argument 'overwrite'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'executeTclCommand'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) r",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) r",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) r",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) referenced +[WARNING ODB-0176] error: undefined layer (metal3) r",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'saveDef'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'saveDb'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'generateVerilog'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Tech' object has no attribute 'loadLiberty' +. Did you mean: 'readLiberty +'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_64x21.lef, created 1 library cells +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_256x32.lef, created 1 library ce",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Tech' object has no attribute 'initializeLef'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 2, in +TypeError: Tech.readLiberty() got an unexpected keyword argument 'verbose'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'saveDesignDef'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'exportDb'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'runTclString' +. Did you mean: 'evalTclString'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Tech' object has no attribute 'importLiberty'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Tech' object has no attribute 'loadLef' +. Did you mean: 'readLef'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_64x21.lef, created 1 library cells +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_256x32.lef, created 1 library ce",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Tech' object has no attribute 'processLef'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'writeDefWithOptions'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'storeDatabase'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'exportVerilog'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Tech' object has no attribute 'addLiberty' +. Did you mean: 'readLiberty'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_64x21.lef, created 1 library cells +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_256x32.lef, created 1 library ce",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_64x21.lef, created 1 library cells +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_256x32.lef, created 1 library ce",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 2, in +TypeError: Tech.readLiberty() got an unexpected keyword argument 'verbose'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'saveDef'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'commitDb'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'executeVerilogCommand'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Tech' object has no attribute 'loadLef' +. Did you mean: 'readLef'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_64x21.lef, created 1 library cells +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_256x32.lef, created 1 library ce",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_64x21.lef, created 1 library cells +[INFO ODB-0227] LEF file: ../Design/nangate45/lef/fakeram45_256x32.lef, created 1 library ce",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"[INFO ODB-0227] LEF file: ../Design/nangate45/lef/NangateOpenCellLibrary.tech.lef, created 22 layers, 27 vias + + + +Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Tech' object has no attribute 'loadLef' +. Did you mean: 'readLef'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'storeDef'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'saveDesign'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILE,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'executeVerilogCommand'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"[WARNING IFP-0028] Core area lower left (5.000, 5.000) snapped to (5.130, 5.600). +[INFO IFP-0001] Added 28 rows of 262 site FreePDK45_38x28_10R_NP_162NW_34O. + +Traceback (most recent call last): + File """", line 1, in +AttributeError: 'InitFloorplan' object has no attribute 'createTrack",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"Traceback (most recent call last): + File """", line 1, in +File ""ifp_py.py"", line 321, in initFloorplan +TypeError: Wrong number or type of arguments for overloaded function 'InitFloorplan_initFloorplan'. + Possible C/C++ prototypes are: + ifp::InitFloorplan::initFloorplan(double,doub",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"[WARNING IFP-0028] Core area lower left (5.000, 5.000) snapped to (5.130, 5.600). +[INFO IFP-0001] Added 28 rows of 262 site FreePDK45_38x28_10R_NP_162NW_34O. + +Traceback (most recent call last): + File """", line 1, in +AttributeError: 'InitFloorplan' object has no attribute 'generateTra",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"Traceback (most recent call last): + File """", line 1, in +File ""ifp_py.py"", line 321, in initFloorplan +TypeError: Wrong number or type of arguments for overloaded function 'InitFloorplan_initFloorplan'. + Possible C/C++ prototypes are: + ifp::InitFloorplan::initFloorplan(double,doub",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"[WARNING IFP-0028] Core area lower left (5.000, 5.000) snapped to (5.130, 5.600). +[INFO IFP-0001] Added 28 rows of 262 site FreePDK45_38x28_10R_NP_162NW_34O. + +Traceback (most recent call last): + File """", line 1, in +AttributeError: 'InitFloorplan' object has no attribute 'setupTracks",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"Traceback (most recent call last): + File """", line 1, in +File ""ifp_py.py"", line 321, in initFloorplan +TypeError: Wrong number or type of arguments for overloaded function 'InitFloorplan_initFloorplan'. + Possible C/C++ prototypes are: + ifp::InitFloorplan::initFloorplan(double,doub",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"[WARNING IFP-0028] Core area lower left (5.000, 5.000) snapped to (5.130, 5.600). +[INFO IFP-0001] Added 28 rows of 262 site FreePDK45_38x28_10R_NP_162NW_34O. + +Traceback (most recent call last): + File """", line 1, in +AttributeError: 'InitFloorplan' object has no attribute 'makeTracksW",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"Traceback (most recent call last): + File """", line 1, in +File ""ifp_py.py"", line 321, in initFloorplan +TypeError: Wrong number or type of arguments for overloaded function 'InitFloorplan_initFloorplan'. + Possible C/C++ prototypes are: + ifp::InitFloorplan::initFloorplan(double,doub",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"[WARNING IFP-0028] Core area lower left (5.000, 5.000) snapped to (5.130, 5.600). +[INFO IFP-0001] Added 28 rows of 262 site FreePDK45_38x28_10R_NP_162NW_34O. + +Traceback (most recent call last): + File """", line 1, in +AttributeError: 'InitFloorplan' object has no attribute 'defineTrack",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"[WARNING IFP-0028] Core area lower left (10.000, 10.000) snapped to (10.070, 11.200). +[INFO IFP-0001] Added 256 rows of 1897 site FreePDK45_38x28_10R_NP_162NW_34O. + +Traceback (most recent call last): + File """", line 1, in +AttributeError: 'InitFloorplan' object has no attribute 'estab",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"[WARNING IFP-0028] Core area lower left (5.000, 5.000) snapped to (5.130, 5.600). +[INFO IFP-0001] Added 28 rows of 262 site FreePDK45_38x28_10R_NP_162NW_34O. + +Traceback (most recent call last): + File """", line 1, in +AttributeError: 'InitFloorplan' object has no attribute 'setupTracks",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FLOORPLAN,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'InitFloorplan' object has no attribute 'runFloorplan' +. Did you mean: 'initFloorplan'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'addHorizontalLayer'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'printConfig'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'obtainTopLayer'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Parameters' object has no attribute 'defineMinSpacing'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'configureHorizontalLength'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'configureVerticalLength'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'addVerticalLayer' +. Did you mean: 'addVerLayer'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'printConfig'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'fetchIOPlacer' +. Did you mean: 'getIOPlacer'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Parameters' object has no attribute 'configureMinDistance'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'setHorizontalLengthWithMode' +. Did you mean: 'setHorizontalLengthExtend'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'updateVerticalLength' +. Did you mean: 'getVerticalLength'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'executeAnnealing'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'printConfig'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'fetchTopLayer' +. Did you mean: 'getTopLayer +'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'setMinDistanceInTracksWithMode' +. Did you mean: 'setMinDistanceInTracks'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +TypeError: Parameters.setHorizontalLength() got an unexpected keyword argument 'mode'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'adjustVerticalLength' +. Did you mean: 'getVerticalLength'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'runAnnealingWithConfig' +. Did you mean: 'setAnnealingConfig'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'printConfig'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'retrieveIOPlacer'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Parameters' object has no attribute 'applyMinDistance' +. Did you mean: 'getMinDistance'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'updateHorizontalLength' +. Did you mean: 'getHorizontalLength'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'applyVerticalLength' +. Did you mean: 'getVerticalLength'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +TypeError: IOPlacer.runAnnealing() takes 2 positional arguments but 3 were given",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'showConfiguration'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'getUpperLayer' +. Did you mean: 'getTopLayer'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Parameters' object has no attribute 'setMinimumSpacing'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'setHorizontalLengthExtended' +. Did you mean: 'setHorizontalLengthExtend'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +TypeError: Parameters.setVerticalLength() takes 2 positional arguments but 3 were given",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'startSimulatedAnnealing'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'printConfig'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'IOPlacer' object has no attribute 'retrieveTopLayerInfo'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 2, in +TypeError: Parameters.setMinDistance() takes 2 positional arguments but 3 were given",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +TypeError: Parameters.setHorizontalLength() got an unexpected keyword argument 'scale'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IO,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Parameters' object has no attribute 'modifyVerticalLength' +. Did you mean: 'getVerticalLength'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GPL,"[INFO GPL-0002] DBU: 2000 +[INFO GPL-0003] SiteSize: ( 0.190 1.400 ) um +[INFO GPL-0004] CoreBBox: ( 10.070 11.200 ) ( 56.430 56.000 ) um +[INFO GPL-0006] NumInstances: 503 +[INFO GPL-0007] NumPlaceInstances: 503 +[INFO GPL-0008] NumFixedInstances: 0 +[INFO GPL-0009] Nu",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GPL,"[INFO GPL-0002] DBU: 2000 +[INFO GPL-0003] SiteSize: ( 0.190 1.400 ) um +[INFO GPL-0004] CoreBBox: ( 10.070 11.200 ) ( 56.430 56.000 ) um +[INFO GPL-0006] NumInstances: 503 +[INFO GPL-0007] NumPlaceInstances: 503 +[INFO GPL-0008] NumFixedInstances: 0 +[INFO GPL-0009] Nu",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GPL,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Replace' object has no attribute 'executeInitialPlacement'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GPL,"[INFO GPL-0002] DBU: 2000 +[INFO GPL-0003] SiteSize: ( 0.190 1.400 ) um +[INFO GPL-0004] CoreBBox: ( 10.070 11.200 ) ( 56.430 56.000 ) um +[INFO GPL-0006] NumInstances: 503 +[INFO GPL-0007] NumPlaceInstances: 503 +[INFO GPL-0008] NumFixedInstances: 0 +[INFO GPL-0009] Nu",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GPL,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Replace' object has no attribute 'setBalancedTargetDensityMode' +. Did you mean: 'setUniformTargetDensityMode'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GPL,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Replace' object has no attribute 'enableUniformDensitySetting'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +MPL,"Traceback (most recent call last): + File """", line 5, in +TypeError: MacroPlacer.placeMacro() got an unexpected keyword argument 'num_threads'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +MPL,"Traceback (most recent call last): + File """", line 5, in +TypeError: MacroPlacer.place() missing 1 required positional argument: 'max_num_macro'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +MPL,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Design' object has no attribute 'macroPlacer' +. Did you mean: 'getMacroPlacer'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +MPL,"Traceback (most recent call last): + File """", line 5, in +TypeError: MacroPlacer.place() missing 1 required positional argument: 'halo_height'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +MPL,"Traceback (most recent call last): + File """", line 5, in +File ""mpl_py.py"", line 238, in place +TypeError: in method 'MacroPlacer_place', argument 30 of type 'int'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +MPL,"Traceback (most recent call last): + File """", line 2, in +AttributeError: 'Design' object has no attribute 'getOpenROADMacroPlacer'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DPL,"Traceback (most recent call last): + File """", line 1, in +File ""dpl_py.py"", line 139, in detailedPlacement +TypeError: Opendp_detailedPlacement expected at most 5 arguments, got 6 +Additional information: +Wrong number or type of arguments for overloaded function 'Opendp_detailedPlacemen",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DPL,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Opendp' object has no attribute 'clearFillers'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DPL,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'dbRow' object has no attribute 'fetchSite' +. Did you mean: 'getSite'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DPL,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Opendp' object has no attribute 'clearFillerCells'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DPL,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Opendp' object has no attribute 'executePlacement' +. Did you mean: 'checkPlacement'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DPL,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Opendp' object has no attribute 'purgeFillers'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"invalid command name ""make_clock""'",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"Traceback (most recent call last): + +File """", line 1, in + +AttributeError +: +'TritonCTS' object has no attribute 'setBufferListWithType'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"invalid command name ""initialize_clock""'",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'TritonCTS' object has no attribute 'assignBufferList' +. Did you mean: 'setBufferList'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"wrong # args: should be ""define_clock_layer_range layers""'",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"Traceback (most recent call last): + File """", line 1, in + +File ""dpl_py.py"", line 139, in detailedPlacement + +TypeError +: +Opendp_detailedPlacement expected at most 5 arguments, got 6 +Additional information: +Wrong number or type of arguments for overloaded function 'Opendp_detailedPlace",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"invalid command name ""setup_clock""'",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"Traceback (most recent call last): +File """", line 1, in + +AttributeError +: +'Opendp' object has no attribute 'advancedDetailedPlacement'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"[ERROR STA-0562] create_clock -target is not a known keyword or flag. +'STA-0562'",OpenROAD执行阶段失败（配置或文件路径问题）,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'TritonCTS' object has no attribute 'configureBufferList'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"invalid command name ""assign_clock""'",未知错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +CTS,"Traceback (most recent call last): + +File """", line 1, in + +AttributeError +: +'TritonCTS' object has no attribute 'setFinalSinkBuffer' +. Did you mean: ' +setSinkBuffer +'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"Traceback (most recent call last): + File """", line 3, in +AttributeError: 'dbMaster' object has no attribute 'getCellType'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"[INFO DPL-0001] Placed 776 filler instances. + + + + + + + +Traceback (most recent call last): + File """", line 4, in +AttributeError: 'dbInst' object has no attribute 'remove'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"Traceback (most recent call last): + File """", line 4, in +TypeError: Opendp.fillerPlacement() got an unexpected keyword argument 'filler_cell_naming_rule'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"[INFO DPL-0001] Placed 776 filler instances. + + + + + + + +Traceback (most recent call last): + File """", line 4, in +AttributeError: 'Design' object has no attribute 'removeFiller'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"Traceback (most recent call last): + File """", line 4, in +TypeError: Opendp.fillerPlacement() got an unexpected keyword argument 'filler_cells'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"[INFO DPL-0001] Placed 776 filler instances. + + + + + + + +Traceback (most recent call last): + File """", line 4, in +AttributeError: 'Design' object has no attribute 'deleteFiller'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"Traceback (most recent call last): + File """", line 4, in +AttributeError: 'Design' object has no attribute 'getOpenROADFillerCellInsert'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"[INFO DPL-0001] Placed 776 filler instances. + + + + + + + + +Traceback (most recent call last): + File """", line 5, in +AttributeError: 'dbInst' object has no attribute 'destory' +. Did you mean: 'destroy'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"Traceback (most recent call last): + File """", line 4, in +AttributeError: 'Opendp' object has no attribute 'fillerInsert'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"[INFO DPL-0001] Placed 776 filler instances. + + + + + + + +Traceback (most recent call last): + File """", line 4, in +AttributeError: 'Design' object has no attribute 'getOpenDp' +. Did you mean: 'getOpendp'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"Traceback (most recent call last): + File """", line 4, in +AttributeError: 'Opendp' object has no attribute 'fillerCellPlacement' +. Did you mean: 'fillerPlacement'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +FILLER,"[INFO DPL-0001] Placed 776 filler instances. + + + + + + + +Traceback (most recent call last): + File """", line 4, in +AttributeError: 'Design' object has no attribute 'getOpenDp' +. Did you mean: 'getOpendp'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + +0 + + + + + + +0 + + + + + + +503 + + + + + + +0 + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 2, in +AttributeError: 'PdnGen' object has no attribute 'createRing'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 74, in +AttributeError: 'PdnGen' object has no attribute",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"Traceback (most recent call last): + File """", line 4, in +AttributeError: 'dbNet' object has no attribute 'assignSigType'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """,Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'PdnGen' object has no attribute 'removeGrid'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + +0 + + + + + + +0 + + + + + + +503 + + + + + + +0 + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 46, in +AttributeError: 'PdnGen' object has no attribute 'connectVia'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 74, in +AttributeError: 'PdnGen' object has no attribute",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 33, in +AttributeError: 'PdnGen' object has no attribute 'createConnect' +. Did you mean: 'm",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 33, in +AttributeError: 'PdnGen' object has no attribute 'createConnect' +. Did you mean: 'm",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'PdnGen' object has no attribute 'disconnectGrid'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + +0 + + + + + + +0 + + + + + + +503 + + + + + + +0 + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 46, in +AttributeError: 'PdnGen' object has no attribute 'connectVia'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 74, in +AttributeError: 'PdnGen' object has no attribute",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 33, in +AttributeError: 'PdnGen' object has no attribute 'connectLayers'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 8, in +TypeError: PdnGen.makeStrap() got an unexpected keyword argument 'alignment'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"Traceback (most recent call last): + File """", line 1, in +TypeError: PdnGen.ripUp() got an unexpected keyword argument 'force'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + +0 + + + + + + +0 + + + + + + +503 + + + + + + +0 + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 3, in +AttributeError: 'PdnGen' object has no attribute 'constructRing'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 74, in +AttributeError: 'PdnGen' object has no attribute",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 33, in +AttributeError: 'PdnGen' object has no attribute 'connectLayers'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 8, in +TypeError: PdnGen.makeStrap() got an unexpected keyword argument 'optimize'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'PdnGen' object has no attribute 'removeGrid'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + +0 + + + + + + +0 + + + + + + +503 + + + + + + +0 + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 18, in +AttributeError: 'PdnGen' object has no attribute 'attachFollowp",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 74, in +AttributeError: 'PdnGen' object has no attribute",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 33, in +AttributeError: 'PdnGen' object has no attribute 'connectLayers'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 33, in +AttributeError: 'PdnGen' object has no attribute 'linkConnect' +. Did you mean: 'mak",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'PdnGen' object has no attribute 'destroyGrid'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'dbBlock' object has no attribute 'addPDNConnect'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 74, in +AttributeError: 'PdnGen' object has no attribute",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 33, in +AttributeError: 'PdnGen' object has no attribute 'establishConnectivity'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"503 + + + + + + + +0 + + + + + + + +0 + + + + + + + +503 + + + + + + + +0 + + + +0 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Traceback (most recent call last): + File """", line 33, in +AttributeError: 'PdnGen' object has no attribute 'linkConnect' +. Did you mean: 'mak",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +PDN,"Traceback (most recent call last): + File """", line 1, in +TypeError: PdnGen.ripUp() got an unexpected keyword argument 'mode'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GRT,"Traceback (most recent call last): + File """", line 1, in +TypeError: GlobalRouter.setAdjustment() takes 2 positional arguments but 3 were given",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GRT,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'GlobalRouter' object has no attribute 'executeGlobalRoute'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GRT,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'GlobalRouter' object has no attribute 'executeGlobalRouting' +. Did you mean: 'boxToGlobalRouting'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GRT,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'GlobalRouter' object has no attribute 'setRoutingVerbose'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GRT,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'GlobalRouter' object has no attribute 'enableVerbosity'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +GRT,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'GlobalRouter' object has no attribute 'enableLogging'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'drt' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"[ERROR DRT-0002] Detailed routing has not been run yet. +Traceback (most recent call last): + File """", line 1, in +File ""drt_py.py"", line 122, in getNumDRVs +RuntimeError: DRT-0002",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'drt' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"[ERROR DRT-0002] Detailed routing has not been run yet. +Traceback (most recent call last): + File """", line 1, in +File ""drt_py.py"", line 122, in getNumDRVs +RuntimeError: DRT-0002",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'drt' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"[ERROR DRT-0002] Detailed routing has not been run yet. +Traceback (most recent call last): + File """", line 1, in +File ""drt_py.py"", line 122, in getNumDRVs +RuntimeError: DRT-0002",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'drt' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'TritonRoute' object has no attribute 'retrieveNumDRVs'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'drt' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"[ERROR DRT-0002] Detailed routing has not been run yet. +Traceback (most recent call last): + File """", line 1, in +File ""drt_py.py"", line 122, in getNumDRVs +RuntimeError: DRT-0002",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'drt' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +DRT,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'TritonRoute' object has no attribute 'getDRVCount'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'psm' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'executeTclCommand'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'psm' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +TypeError: Design.evalTclString() got an unexpected keyword argument 'detailed'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'psm' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'executePowerReport'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'psm' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +TypeError: Design.evalTclString() got an unexpected keyword argument 'level'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'psm' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +AttributeError: 'Design' object has no attribute 'evalTclScript' +. Did you mean: 'evalTclString'?",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +NameError: name 'psm' is not defined",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, +IR,"Traceback (most recent call last): + File """", line 1, in +TypeError: Design.evalTclString() got an unexpected keyword argument 'mode'",Python语法或API调用错误,检查模块初始化顺序、输入文件路径、API调用参数是否正确。可参考相应的正确脚本示例。, diff --git a/flow-Agent/rag_data/docs.pkl b/flow-Agent/rag_data/docs.pkl new file mode 100644 index 0000000000000000000000000000000000000000..6a4ac25b04e680c5b97ea255e6c0f58b5136cce2 GIT binary patch literal 297319 zcmeFadyr&Ve%~b_5ylgiFky#51VP*wBu({hWp&TY&hG38d8w|d?kP`ocWqVmOs_W9 zNmgc7Rc>cx*5;#odL-7alF$ z>G03bzExZu^|}Yeakm%_id!e$!OpGK_2OE8c>gmmt-h5$X&mrLW85C~PA21G>DJD* z-AhGpT(pXVX}|xVXiX=>!SHxE9WNI${tqg?>~V3`fPNb<*n;tx@}^H|e$~ z(^0o*4LU`qJMJA0it$OS-7UKBpY(^L)}%KaEEnC@h*eKU-A=EqPm19|@!8?da`@S# 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