# SGR Search Log: infinigen_seed
Total time: 17.4s
---
## Step 1: start (+0.0s)
**question:**
```
Find the init.py file where apply_scene_seed function sets numpy random seed
```
**repo_path:**
```
/Users/mix0z/PycharmProjects/Semantic-Search-MCP/data/issues/infinigen/repo
```
**expected_files:**
```
[
"infinigen/core/init.py"
]
```
## Step 2: analyze_repo_start (+0.0s)
**repo_path:**
```
/Users/mix0z/PycharmProjects/Semantic-Search-MCP/data/issues/infinigen/repo
```
## Step 3: log (+0.0s)
**message:**
```
Step 0: Analyzing repository context (smart)...
```
## Step 4: log (+0.0s)
**message:**
```
[Tool] analyze_repo_smart: scanning repository...
```
## Step 5: log (+0.0s)
**message:**
```
Languages found: {'Python': 878, 'C++': 46, 'C': 45}
```
## Step 6: log (+0.0s)
**message:**
```
Primary (detected): Python
```
## Step 7: log (+0.0s)
**message:**
```
Framework (detected): None
```
## Step 8: log (+0.0s)
**message:**
```
Top dirs: ['docs', 'infinigen', 'infinigen_examples', 'scripts', 'tests']
```
## Step 9: log (+0.0s)
**message:**
```
Manifests: ['requirements.txt', 'pyproject.toml', 'setup.py']
```
## Step 10: log (+0.0s)
**message:**
```
[Tool] list_dir: .
```
## Step 11: llm_call_start (+0.0s)
**response_format:**
```
RepoContext
```
**messages:**
```
[
{
"role": "system",
"content": "You are a code repository analyst. Analyze the repository structure to understand:\n\n1. PRIMARY LANGUAGE: What programming language is mainly used?\n - Look at file extensions: .py (Python), .go (Go), .java (Java), .ts/.js (JavaScript/TypeScript)\n - Check for package files: requirements.txt, go.mod, pom.xml, package.json\n\n2. FRAMEWORK: What framework or library is this?\n - Python web: Flask, FastAPI, Tornado, Pyramid\n - JavaScript: Express, Koa, NestJS, React, Vue, Angular\n - Go: Standard library, Echo, Fiber, Chi\n - Java: Spring, Micronaut, Quarkus, Vert.x\n - Or is it a standalone library/tool?\n\n3. PROJECT TYPE:\n - web_framework: HTTP server, REST API\n - library: Reusable package/SDK\n - cli_tool: Command-line application\n - desktop_app: GUI application\n - data_science: ML/Data processing\n - game_engine: Graphics/Game\n - other\n\n4. KEY DIRECTORIES: Important folders for searching\n - Look for:
...
```
## Step 12: log (+1.4s)
**message:**
```
Gemini call took 1376ms
```
## Step 13: llm_response (+1.4s)
**response_format:**
```
RepoContext
```
**result:**
```
{
"primary_language": "Python",
"languages": {},
"framework": "other",
"project_type": "other",
"key_directories": [
"infinigen/",
"tests/",
"infinigen_examples/",
"scripts/"
],
"file_patterns": [
"*.py",
"*.cpp",
"*.c",
"*.txt",
"*.md"
],
"naming_conventions": "unknown"
}
```
## Step 14: log (+1.4s)
**message:**
```
[Smart] Key dirs by source count: ['infinigen/', 'tests/', 'infinigen_examples/', 'scripts/']...
```
## Step 15: log (+1.4s)
**message:**
```
Final Language: Python
```
## Step 16: log (+1.4s)
**message:**
```
Final Languages: {'Python': 878, 'C++': 46, 'C': 45}
```
## Step 17: log (+1.4s)
**message:**
```
Final Framework: other
```
## Step 18: log (+1.4s)
**message:**
```
Final Type: other
```
## Step 19: log (+1.4s)
**message:**
```
Final Key dirs: ['infinigen/', 'tests/', 'infinigen_examples/', 'scripts/']
```
## Step 20: analyze_repo_result (+1.4s)
**primary_language:**
```
Python
```
**framework:**
```
other
```
**project_type:**
```
other
```
**key_directories:**
```
[
"infinigen/",
"tests/",
"infinigen_examples/",
"scripts/"
]
```
## Step 21: analyze_question_start (+1.4s)
**query:**
```
Find the init.py file where apply_scene_seed function sets numpy random seed
```
**repo_hint:**
```
repo
```
## Step 22: log (+1.4s)
**message:**
```
Step 1: Analyzing question concepts...
```
## Step 23: llm_call_start (+1.4s)
**response_format:**
```
QuestionAnalysis
```
**messages:**
```
[
{
"role": "system",
"content": "You are a code search expert analyzing a question about a codebase.\n\nYour task: Extract HIGH-LEVEL CONCEPTS from the question.\nDo NOT generate grep patterns yet - that's the next step.\n\nFocus on understanding:\n\n1. What CONCEPTS is the user asking about?\n Examples of concepts (abstract ideas, not code):\n - \"authentication flow\" - how users log in\n - \"caching mechanism\" - how data is cached\n - \"event handling\" - how events are processed\n - \"error propagation\" - how errors bubble up\n - \"connection pooling\" - how connections are reused\n - \"state management\" - how state is stored/updated\n - \"request lifecycle\" - how requests are processed\n \n2. What PROBLEM is the user trying to solve?\n - Summarize their goal in 1-2 sentences\n\n3. What CODE do they need to find?\n - Be specific: \"the code that handles X\"\n\n4. What TYPE of question is this?\n - how_it_works: Understanding implementation\n
...
```
## Step 24: log (+2.4s)
**message:**
```
Gemini call took 1010ms
```
## Step 25: llm_response (+2.4s)
**response_format:**
```
QuestionAnalysis
```
**result:**
```
{
"concepts": [
"numpy random seed",
"apply_scene_seed function",
"init.py file"
],
"user_problem": "The user wants to find the specific file `init.py` where a function `apply_scene_seed` is located and potentially modifies the numpy random seed.",
"what_to_find": "The init.py file where the apply_scene_seed function sets the numpy random seed",
"question_type": "where_is_it"
}
```
## Step 26: log (+2.4s)
**message:**
```
Concepts: ['numpy random seed', 'apply_scene_seed function', 'init.py file']
```
## Step 27: log (+2.4s)
**message:**
```
User problem: The user wants to find the specific file `init.py` where a function `apply_scene_seed` is located and potentially modifies the numpy random seed.
```
## Step 28: log (+2.4s)
**message:**
```
What to find: The init.py file where the apply_scene_seed function sets the numpy random seed
```
## Step 29: log (+2.4s)
**message:**
```
Question type: where_is_it
```
## Step 30: analyze_question_result (+2.4s)
**question_type:**
```
where_is_it
```
**concepts:**
```
[
"numpy random seed",
"apply_scene_seed function",
"init.py file"
]
```
**user_problem:**
```
The user wants to find the specific file `init.py` where a function `apply_scene_seed` is located and potentially modifies the numpy random seed.
```
**what_to_find:**
```
The init.py file where the apply_scene_seed function sets the numpy random seed
```
## Step 31: log (+2.4s)
**message:**
```
Step 2: Extracting technical terms...
```
## Step 32: log (+2.4s)
**message:**
```
Exploring actual directory structure...
```
## Step 33: log (+2.4s)
**message:**
```
[Tool] list_dir: .
```
## Step 34: log (+2.4s)
**message:**
```
[Tool] list_dir: infinigen/
```
## Step 35: log (+2.4s)
**message:**
```
[Tool] list_dir: tests/
```
## Step 36: log (+2.4s)
**message:**
```
[Tool] list_dir: infinigen_examples/
```
## Step 37: log (+2.4s)
**message:**
```
[Tool] list_dir: scripts/
```
## Step 38: log (+2.4s)
**message:**
```
Explored 4 key directories
```
## Step 39: llm_call_start (+2.4s)
**response_format:**
```
TechnicalTerms
```
**messages:**
```
[
{
"role": "system",
"content": "You are a code search expert generating search terms.\n\nYou have TWO sources of information:\n1. The question concepts (what user wants to find)\n2. ACTUAL directory/file structure from the repository\n\nYOUR JOB: Match question concepts to REAL files/modules you see in the structure.\n\n=== HOW TO EXTRACT TERMS ===\n\nLook at the ACTUAL directory listing and extract terms from it:\n\n1. FROM FOLDER NAMES:\n - See \"auth/\" \u2192 use \"auth\" as search term\n - See \"cache/\" \u2192 use \"cache\" as search term\n - See \"handlers/\" \u2192 use \"handler\" as search term\n - See \"services/\" \u2192 use \"service\" as search term\n\n2. FROM FILE NAMES:\n - See \"user_manager.py\" \u2192 use \"user_manager\", \"Manager\"\n - See \"connection_pool.go\" \u2192 use \"connection_pool\", \"Pool\"\n - See \"EventBus.java\" \u2192 use \"EventBus\", \"Bus\"\n - See \"rate_limiter.ts\" \u2192 use \"rate_limiter\", \"limiter\"\n\n3. FRO
...
```
## Step 40: log (+4.2s)
**message:**
```
Gemini call took 1762ms
```
## Step 41: llm_response (+4.2s)
**response_format:**
```
TechnicalTerms
```
**result:**
```
{
"primary_terms": [
{
"term": "apply_scene_seed",
"term_type": "function_name",
"confidence": "high",
"reasoning": "The user is explicitly asking to find the function 'apply_scene_seed'."
},
{
"term": "numpy",
"term_type": "class_name",
"confidence": "high",
"reasoning": "The user mentions 'numpy random seed', indicating a dependency on the numpy library."
},
{
"term": "seed",
"term_type": "variable_name",
"confidence": "medium",
"reasoning": "The user is looking for where 'seed' is set, and 'seed' is a common variable name for this purpose. It's also mentioned in conjunction with 'numpy random seed'."
}
],
"secondary_terms": [
{
"term": "__init__",
"term_type": "file_name",
"confidence": "low",
"reasoning": "The user specifically mentioned 'init.py file', making it a relevant search term, although it's a very generic file name."
},
{
"term":
...
```
## Step 42: log (+4.2s)
**message:**
```
Primary terms: ['apply_scene_seed', 'numpy', 'seed']
```
## Step 43: log (+4.2s)
**message:**
```
Secondary terms: ['__init__', 'random']
```
## Step 44: log (+4.2s)
**message:**
```
Likely files: ['infinigen/core/init.py', 'infinigen_examples/__init__.py']
```
## Step 45: log (+4.2s)
**message:**
```
Step 2.5: Reading 2 likely files...
```
## Step 46: log (+4.2s)
**message:**
```
[Tool] read_file: infinigen/core/init.py
```
## Step 47: log (+4.2s)
**message:**
```
[Read] infinigen/core/init.py: 8 definitions found
```
## Step 48: log (+4.2s)
**message:**
```
[Tool] read_file: infinigen_examples/__init__.py
```
## Step 49: log (+4.2s)
**message:**
```
Extracted 8 findings from likely files
```
## Step 50: log (+4.2s)
**message:**
```
Step 3: Creating search plan...
```
## Step 51: llm_call_start (+4.2s)
**response_format:**
```
TypedSearchPlan
```
**messages:**
```
[
{
"role": "system",
"content": "Create a search plan using the technical terms identified.\n\nYou MUST create actions with ALL REQUIRED FIELDS filled in.\n\n=== GREP ACTIONS ===\nSearch file contents. \"pattern\" is REQUIRED.\nFields:\n- pattern: REQUIRED - regex to search (e.g., \"QuerySet\", \"class.*Handler\")\n- path: optional - directory to search in\n- glob: optional - file filter (e.g., \"*.py\")\n- purpose: what you're looking for\n\n=== READ_FILE ACTIONS ===\nRead specific file. \"file_path\" is REQUIRED.\nFields:\n- file_path: REQUIRED - path to file (e.g., \"django/db/models/query.py\")\n- start_line/end_line: optional - line range\n- purpose: why reading this file\n\n=== LIST_DIR ACTIONS ===\nExplore directory structure.\nFields:\n- path: directory to list (default \".\")\n- max_depth: depth limit (default 2)\n- purpose: what structure to discover\n\n=== GLOB_SEARCH ACTIONS ===\nFind files by name. \"pattern\" is REQUIRED.\nFields:\n- pattern: REQUIRED - glob pa
...
```
## Step 52: log (+5.4s)
**message:**
```
Gemini call took 1213ms
```
## Step 53: llm_response (+5.4s)
**response_format:**
```
TypedSearchPlan
```
**result:**
```
{
"strategy": "keyword_hunt",
"grep_actions": [
{
"purpose": "Find the apply_scene_seed function",
"expected_result": "Find relevant code",
"tool": "grep",
"pattern": "def apply_scene_seed",
"path": null,
"glob": "**/__init__.py",
"case_insensitive": false,
"context_lines": 3
}
],
"read_file_actions": [
{
"purpose": "Examine init.py for numpy random seed setting",
"expected_result": "Understand how numpy random seed is set in apply_scene_seed",
"tool": "read_file",
"file_path": "infinigen/core/__init__.py",
"start_line": null,
"end_line": null
}
],
"list_dir_actions": [],
"glob_search_actions": [],
"strategy_reasoning": "The user is asking to find a specific function and understand its implementation related to setting a numpy random seed. The `keyword_hunt` strategy is suitable here, and I will use `grep` to find the function and `read_file` to inspect the relevant file.
...
```
## Step 54: log (+5.4s)
**message:**
```
TypedSearchPlan: 1 grep, 1 read, 0 list, 0 glob
```
## Step 55: log (+5.4s)
**message:**
```
Strategy: keyword_hunt
```
## Step 56: log (+5.4s)
**message:**
```
Actions: 2 (from TypedSearchPlan)
```
## Step 57: log (+5.4s)
**message:**
```
1. grep: def apply_scene_seed - Find the apply_scene_seed function
```
## Step 58: log (+5.4s)
**message:**
```
2. read_file: infinigen/core/__init__.py - Examine init.py for numpy random seed setting
```
## Step 59: log (+5.4s)
**message:**
```
Executing 2 initial actions in parallel...
```
## Step 60: log (+5.4s)
**message:**
```
[Tool] grep: rg --json -C 3 --glob **/__init__.py -m 50 def apply_scene_seed /Users/mix0z/PycharmProjects/Semantic-Search-MCP/data/issues/infinigen/repo
```
## Step 61: log (+8.4s)
**message:**
```
[Tool] read_file: infinigen/core/__init__.py
```
## Step 62: log (+8.5s)
**message:**
```
Step 3: Interpreting result...
```
## Step 63: llm_call_start (+8.5s)
**response_format:**
```
SearchResultInterpretation
```
**messages:**
```
[
{
"role": "system",
"content": "Interpret the search result and decide next steps.\n\nAnalyze:\n1. Did we find anything relevant to the question?\n2. What are the key findings (files, functions, classes)?\n3. What new search directions emerged?\n4. How confident are we this is the right direction?\n5. Do we need more searches or are we ready to answer?\n\nEXTRACTING FINDINGS:\n- Note COMPLETE file paths exactly as shown in the result (e.g., 'src/core/handlers/base.py' not just 'base.py')\n- Note class/function names found\n- Note any imports or references to other files\n\nCONFIDENCE LEVELS:\n- HIGH: Found the exact implementation, clear answer\n- MEDIUM: Found related code, need to verify\n- LOW: Found nothing or unrelated results\n\nCRITICAL PATH REQUIREMENT:\n- ALWAYS use the FULL file path including all directory prefixes\n- NEVER shorten paths: use 'bin/hive-mind/memory.js' NOT 'memory.js'\n- Copy the path EXACTLY as it appears in the search result\n- Format findings a
...
```
## Step 64: log (+9.0s)
**message:**
```
Gemini call took 543ms
```
## Step 65: llm_response (+9.0s)
**response_format:**
```
SearchResultInterpretation
```
**result:**
```
{
"action_executed": "grep",
"found_relevant": false,
"key_findings": [],
"new_leads": [],
"confidence": "low",
"next_action_needed": true
}
```
## Step 66: log (+9.0s)
**message:**
```
Found relevant: False
```
## Step 67: log (+9.0s)
**message:**
```
Key findings: []
```
## Step 68: log (+9.0s)
**message:**
```
Confidence: low
```
## Step 69: log (+9.0s)
**message:**
```
Need more: True
```
## Step 70: log (+9.0s)
**message:**
```
Step 3: Interpreting result...
```
## Step 71: llm_call_start (+9.0s)
**response_format:**
```
SearchResultInterpretation
```
**messages:**
```
[
{
"role": "system",
"content": "Interpret the search result and decide next steps.\n\nAnalyze:\n1. Did we find anything relevant to the question?\n2. What are the key findings (files, functions, classes)?\n3. What new search directions emerged?\n4. How confident are we this is the right direction?\n5. Do we need more searches or are we ready to answer?\n\nEXTRACTING FINDINGS:\n- Note COMPLETE file paths exactly as shown in the result (e.g., 'src/core/handlers/base.py' not just 'base.py')\n- Note class/function names found\n- Note any imports or references to other files\n\nCONFIDENCE LEVELS:\n- HIGH: Found the exact implementation, clear answer\n- MEDIUM: Found related code, need to verify\n- LOW: Found nothing or unrelated results\n\nCRITICAL PATH REQUIREMENT:\n- ALWAYS use the FULL file path including all directory prefixes\n- NEVER shorten paths: use 'bin/hive-mind/memory.js' NOT 'memory.js'\n- Copy the path EXACTLY as it appears in the search result\n- Format findings a
...
```
## Step 72: log (+9.5s)
**message:**
```
Gemini call took 528ms
```
## Step 73: llm_response (+9.5s)
**response_format:**
```
SearchResultInterpretation
```
**result:**
```
{
"action_executed": "read_file",
"found_relevant": false,
"key_findings": [],
"new_leads": [],
"confidence": "low",
"next_action_needed": true
}
```
## Step 74: log (+9.5s)
**message:**
```
Found relevant: False
```
## Step 75: log (+9.5s)
**message:**
```
Key findings: []
```
## Step 76: log (+9.5s)
**message:**
```
Confidence: low
```
## Step 77: log (+9.5s)
**message:**
```
Need more: True
```
## Step 78: llm_call_start (+9.5s)
**response_format:**
```
NextActionDecision
```
**messages:**
```
[
{
"role": "system",
"content": "Decide whether to continue searching or generate the final answer.\n\nConsider:\n1. Have we found enough information to answer the question?\n2. Are there promising leads we haven't followed?\n3. Have we been searching too long without progress?\n4. Did we reach HIGH confidence in any iteration?\n\nCONTINUE SEARCHING if:\n- Found file references but haven't read them\n- Found a folder but haven't searched inside it\n- Primary terms didn't work, try secondary terms\n- Found imports pointing to other files\n\nSTOP SEARCHING if:\n- Found the core implementation with HIGH confidence\n- Searched 5+ iterations without progress\n- All terms exhausted with no results\n\nSPECIFYING NEXT ACTION - Use these FLAT FIELDS:\n1. Set has_next_action=true\n2. Set next_action_tool to one of: \"grep\", \"read_file\", \"list_dir\", \"glob_search\"\n3. Fill the REQUIRED field for your tool:\n\n For grep:\n - grep_pattern: \"your_search_term\" (REQUIRED)\n
...
```
## Step 79: llm_call_start (+9.5s)
**response_format:**
```
NextActionDecision
```
**messages:**
```
[
{
"role": "system",
"content": "Decide whether to continue searching or generate the final answer.\n\nConsider:\n1. Have we found enough information to answer the question?\n2. Are there promising leads we haven't followed?\n3. Have we been searching too long without progress?\n4. Did we reach HIGH confidence in any iteration?\n\nCONTINUE SEARCHING if:\n- Found file references but haven't read them\n- Found a folder but haven't searched inside it\n- Primary terms didn't work, try secondary terms\n- Found imports pointing to other files\n\nSTOP SEARCHING if:\n- Found the core implementation with HIGH confidence\n- Searched 5+ iterations without progress\n- All terms exhausted with no results\n\nSPECIFYING NEXT ACTION - Use these FLAT FIELDS:\n1. Set has_next_action=true\n2. Set next_action_tool to one of: \"grep\", \"read_file\", \"list_dir\", \"glob_search\"\n3. Fill the REQUIRED field for your tool:\n\n For grep:\n - grep_pattern: \"your_search_term\" (REQUIRED)\n
...
```
## Step 80: llm_call_start (+9.5s)
**response_format:**
```
NextActionDecision
```
**messages:**
```
[
{
"role": "system",
"content": "Decide whether to continue searching or generate the final answer.\n\nConsider:\n1. Have we found enough information to answer the question?\n2. Are there promising leads we haven't followed?\n3. Have we been searching too long without progress?\n4. Did we reach HIGH confidence in any iteration?\n\nCONTINUE SEARCHING if:\n- Found file references but haven't read them\n- Found a folder but haven't searched inside it\n- Primary terms didn't work, try secondary terms\n- Found imports pointing to other files\n\nSTOP SEARCHING if:\n- Found the core implementation with HIGH confidence\n- Searched 5+ iterations without progress\n- All terms exhausted with no results\n\nSPECIFYING NEXT ACTION - Use these FLAT FIELDS:\n1. Set has_next_action=true\n2. Set next_action_tool to one of: \"grep\", \"read_file\", \"list_dir\", \"glob_search\"\n3. Fill the REQUIRED field for your tool:\n\n For grep:\n - grep_pattern: \"your_search_term\" (REQUIRED)\n
...
```
## Step 81: log (+10.4s)
**message:**
```
Gemini call took 826ms
```
## Step 82: llm_response (+10.4s)
**response_format:**
```
NextActionDecision
```
**result:**
```
{
"should_continue": false,
"reason": "",
"ready_for_answer": false,
"has_next_action": true,
"next_action_tool": "read_file",
"grep_pattern": null,
"grep_path": null,
"file_path": "infinigen/core/__init__.py",
"list_dir_path": null,
"glob_pattern": null,
"glob_path": null,
"next_action_purpose": "Read the file to find the implementation of apply_scene_seed and check if it sets numpy random seed.",
"next_action_expected": "The implementation of apply_scene_seed and whether it sets numpy random seed.",
"next_action_params": null
}
```
## Step 83: log (+10.5s)
**message:**
```
Gemini call took 925ms
```
## Step 84: llm_response (+10.5s)
**response_format:**
```
NextActionDecision
```
**result:**
```
{
"should_continue": false,
"reason": "",
"ready_for_answer": false,
"has_next_action": true,
"next_action_tool": "grep",
"grep_pattern": "numpy.random.seed",
"grep_path": "infinigen/core/__init__.py",
"file_path": null,
"list_dir_path": null,
"glob_pattern": null,
"glob_path": null,
"next_action_purpose": "Search for the numpy random seed function call within the apply_scene_seed function.",
"next_action_expected": "The line of code where numpy random seed is set.",
"next_action_params": null
}
```
## Step 85: log (+10.6s)
**message:**
```
Gemini call took 1077ms
```
## Step 86: llm_response (+10.6s)
**response_format:**
```
NextActionDecision
```
**result:**
```
{
"should_continue": false,
"reason": "",
"ready_for_answer": false,
"has_next_action": true,
"next_action_tool": "grep",
"grep_pattern": "numpy.random.seed",
"grep_path": null,
"file_path": null,
"list_dir_path": null,
"glob_pattern": null,
"glob_path": null,
"next_action_purpose": "Search for the numpy random seed setting within the apply_scene_seed function.",
"next_action_expected": "The line of code where numpy.random.seed is called within apply_scene_seed",
"next_action_params": null
}
```
## Step 87: log (+10.6s)
**message:**
```
[Aggregation] 3 valid actions, 0 stop, 0 invalid
```
## Step 88: log (+10.6s)
**message:**
```
Iteration 3: grep
```
## Step 89: log (+10.6s)
**message:**
```
[Tool] grep: rg --json -C 3 -m 50 numpy.random.seed /Users/mix0z/PycharmProjects/Semantic-Search-MCP/data/issues/infinigen/repo/infinigen/core/__init__.py
```
## Step 90: log (+10.6s)
**message:**
```
Step 3: Interpreting result...
```
## Step 91: llm_call_start (+10.6s)
**response_format:**
```
SearchResultInterpretation
```
**messages:**
```
[
{
"role": "system",
"content": "Interpret the search result and decide next steps.\n\nAnalyze:\n1. Did we find anything relevant to the question?\n2. What are the key findings (files, functions, classes)?\n3. What new search directions emerged?\n4. How confident are we this is the right direction?\n5. Do we need more searches or are we ready to answer?\n\nEXTRACTING FINDINGS:\n- Note COMPLETE file paths exactly as shown in the result (e.g., 'src/core/handlers/base.py' not just 'base.py')\n- Note class/function names found\n- Note any imports or references to other files\n\nCONFIDENCE LEVELS:\n- HIGH: Found the exact implementation, clear answer\n- MEDIUM: Found related code, need to verify\n- LOW: Found nothing or unrelated results\n\nCRITICAL PATH REQUIREMENT:\n- ALWAYS use the FULL file path including all directory prefixes\n- NEVER shorten paths: use 'bin/hive-mind/memory.js' NOT 'memory.js'\n- Copy the path EXACTLY as it appears in the search result\n- Format findings a
...
```
## Step 92: log (+11.5s)
**message:**
```
Gemini call took 914ms
```
## Step 93: llm_response (+11.5s)
**response_format:**
```
SearchResultInterpretation
```
**result:**
```
{
"action_executed": "grep",
"found_relevant": false,
"key_findings": [],
"new_leads": [],
"confidence": "low",
"next_action_needed": true
}
```
## Step 94: log (+11.5s)
**message:**
```
Found relevant: False
```
## Step 95: log (+11.5s)
**message:**
```
Key findings: []
```
## Step 96: log (+11.5s)
**message:**
```
Confidence: low
```
## Step 97: log (+11.5s)
**message:**
```
Need more: True
```
## Step 98: llm_call_start (+11.5s)
**response_format:**
```
NextActionDecision
```
**messages:**
```
[
{
"role": "system",
"content": "Decide whether to continue searching or generate the final answer.\n\nConsider:\n1. Have we found enough information to answer the question?\n2. Are there promising leads we haven't followed?\n3. Have we been searching too long without progress?\n4. Did we reach HIGH confidence in any iteration?\n\nCONTINUE SEARCHING if:\n- Found file references but haven't read them\n- Found a folder but haven't searched inside it\n- Primary terms didn't work, try secondary terms\n- Found imports pointing to other files\n\nSTOP SEARCHING if:\n- Found the core implementation with HIGH confidence\n- Searched 5+ iterations without progress\n- All terms exhausted with no results\n\nSPECIFYING NEXT ACTION - Use these FLAT FIELDS:\n1. Set has_next_action=true\n2. Set next_action_tool to one of: \"grep\", \"read_file\", \"list_dir\", \"glob_search\"\n3. Fill the REQUIRED field for your tool:\n\n For grep:\n - grep_pattern: \"your_search_term\" (REQUIRED)\n
...
```
## Step 99: llm_call_start (+11.6s)
**response_format:**
```
NextActionDecision
```
**messages:**
```
[
{
"role": "system",
"content": "Decide whether to continue searching or generate the final answer.\n\nConsider:\n1. Have we found enough information to answer the question?\n2. Are there promising leads we haven't followed?\n3. Have we been searching too long without progress?\n4. Did we reach HIGH confidence in any iteration?\n\nCONTINUE SEARCHING if:\n- Found file references but haven't read them\n- Found a folder but haven't searched inside it\n- Primary terms didn't work, try secondary terms\n- Found imports pointing to other files\n\nSTOP SEARCHING if:\n- Found the core implementation with HIGH confidence\n- Searched 5+ iterations without progress\n- All terms exhausted with no results\n\nSPECIFYING NEXT ACTION - Use these FLAT FIELDS:\n1. Set has_next_action=true\n2. Set next_action_tool to one of: \"grep\", \"read_file\", \"list_dir\", \"glob_search\"\n3. Fill the REQUIRED field for your tool:\n\n For grep:\n - grep_pattern: \"your_search_term\" (REQUIRED)\n
...
```
## Step 100: llm_call_start (+11.6s)
**response_format:**
```
NextActionDecision
```
**messages:**
```
[
{
"role": "system",
"content": "Decide whether to continue searching or generate the final answer.\n\nConsider:\n1. Have we found enough information to answer the question?\n2. Are there promising leads we haven't followed?\n3. Have we been searching too long without progress?\n4. Did we reach HIGH confidence in any iteration?\n\nCONTINUE SEARCHING if:\n- Found file references but haven't read them\n- Found a folder but haven't searched inside it\n- Primary terms didn't work, try secondary terms\n- Found imports pointing to other files\n\nSTOP SEARCHING if:\n- Found the core implementation with HIGH confidence\n- Searched 5+ iterations without progress\n- All terms exhausted with no results\n\nSPECIFYING NEXT ACTION - Use these FLAT FIELDS:\n1. Set has_next_action=true\n2. Set next_action_tool to one of: \"grep\", \"read_file\", \"list_dir\", \"glob_search\"\n3. Fill the REQUIRED field for your tool:\n\n For grep:\n - grep_pattern: \"your_search_term\" (REQUIRED)\n
...
```
## Step 101: log (+12.4s)
**message:**
```
Gemini call took 893ms
```
## Step 102: llm_response (+12.4s)
**response_format:**
```
NextActionDecision
```
**result:**
```
{
"should_continue": false,
"reason": "",
"ready_for_answer": false,
"has_next_action": true,
"next_action_tool": "grep",
"grep_pattern": "numpy.random.seed",
"grep_path": "infinigen/core/__init__.py",
"file_path": null,
"list_dir_path": null,
"glob_pattern": null,
"glob_path": null,
"next_action_purpose": "Search for numpy random seed within the apply_scene_seed function in infinigen/core/__init__.py",
"next_action_expected": "The line of code where numpy.random.seed is called within apply_scene_seed",
"next_action_params": null
}
```
## Step 103: log (+12.7s)
**message:**
```
Gemini call took 1192ms
```
## Step 104: llm_response (+12.7s)
**response_format:**
```
NextActionDecision
```
**result:**
```
{
"should_continue": false,
"reason": "",
"ready_for_answer": false,
"has_next_action": true,
"next_action_tool": "grep",
"grep_pattern": "numpy.random.seed",
"grep_path": "infinigen/core/__init__.py",
"file_path": null,
"list_dir_path": null,
"glob_pattern": null,
"glob_path": null,
"next_action_purpose": "Search for numpy random seed setting within the apply_scene_seed function.",
"next_action_expected": "The line of code where numpy random seed is set.",
"next_action_params": null
}
```
## Step 105: log (+12.8s)
**message:**
```
Gemini call took 1283ms
```
## Step 106: llm_response (+12.8s)
**response_format:**
```
NextActionDecision
```
**result:**
```
{
"should_continue": false,
"reason": "",
"ready_for_answer": false,
"has_next_action": true,
"next_action_tool": "grep",
"grep_pattern": "numpy.random.seed",
"grep_path": "infinigen/core/__init__.py",
"file_path": null,
"list_dir_path": null,
"glob_pattern": null,
"glob_path": null,
"next_action_purpose": "Search for numpy random seed call within the apply_scene_seed function in the __init__.py file.",
"next_action_expected": "The line of code where numpy.random.seed is called within apply_scene_seed",
"next_action_params": null
}
```
## Step 107: log (+12.8s)
**message:**
```
[Aggregation] 3 valid actions, 0 stop, 0 invalid
```
## Step 108: log (+12.8s)
**message:**
```
Iteration 4: grep
```
## Step 109: log (+12.8s)
**message:**
```
[Tool] grep: rg --json -C 3 -m 50 numpy.random.seed /Users/mix0z/PycharmProjects/Semantic-Search-MCP/data/issues/infinigen/repo/infinigen/core/__init__.py
```
## Step 110: log (+13.8s)
**message:**
```
Step 3: Interpreting result...
```
## Step 111: llm_call_start (+13.8s)
**response_format:**
```
SearchResultInterpretation
```
**messages:**
```
[
{
"role": "system",
"content": "Interpret the search result and decide next steps.\n\nAnalyze:\n1. Did we find anything relevant to the question?\n2. What are the key findings (files, functions, classes)?\n3. What new search directions emerged?\n4. How confident are we this is the right direction?\n5. Do we need more searches or are we ready to answer?\n\nEXTRACTING FINDINGS:\n- Note COMPLETE file paths exactly as shown in the result (e.g., 'src/core/handlers/base.py' not just 'base.py')\n- Note class/function names found\n- Note any imports or references to other files\n\nCONFIDENCE LEVELS:\n- HIGH: Found the exact implementation, clear answer\n- MEDIUM: Found related code, need to verify\n- LOW: Found nothing or unrelated results\n\nCRITICAL PATH REQUIREMENT:\n- ALWAYS use the FULL file path including all directory prefixes\n- NEVER shorten paths: use 'bin/hive-mind/memory.js' NOT 'memory.js'\n- Copy the path EXACTLY as it appears in the search result\n- Format findings a
...
```
## Step 112: log (+14.5s)
**message:**
```
Gemini call took 760ms
```
## Step 113: llm_response (+14.5s)
**response_format:**
```
SearchResultInterpretation
```
**result:**
```
{
"action_executed": "grep numpy.random.seed in infinigen/core/__init__.py",
"found_relevant": true,
"key_findings": [
"infinigen/core/__init__.py:152: find_config"
],
"new_leads": [
"numpy.random.seed is not directly in apply_scene_seed, need to find where apply_scene_seed is defined and if it calls another function that sets the seed"
],
"confidence": "high",
"next_action_needed": true
}
```
## Step 114: log (+14.5s)
**message:**
```
Found relevant: True
```
## Step 115: log (+14.5s)
**message:**
```
Key findings: ['infinigen/core/__init__.py:152: find_config']
```
## Step 116: log (+14.5s)
**message:**
```
Confidence: high
```
## Step 117: log (+14.5s)
**message:**
```
Need more: True
```
## Step 118: log (+14.5s)
**message:**
```
High confidence with relevant findings - stopping search
```
## Step 119: log (+14.5s)
**message:**
```
Step 5: Generating final answer...
```
## Step 120: llm_call_start (+14.5s)
**response_format:**
```
FinalAnswer
```
**messages:**
```
[
{
"role": "system",
"content": "Generate a final answer based on the search results.\n\nInclude:\n1. SUMMARY: Clear answer to the question (what code does what, where it is)\n2. CODE LOCATIONS: Specific file paths with relevant functions/classes\n3. REASONING CHAIN: Steps taken to find the answer\n4. CONFIDENCE: How confident you are\n5. POTENTIAL GAPS: What might have been missed\n\nCRITICAL for CODE LOCATIONS (file_path field):\n- Use COMPLETE file paths exactly as shown in the findings\n- NEVER use just the filename: 'memory.js' is WRONG\n- ALWAYS include directory prefix: 'bin/hive-mind/memory.js' is CORRECT\n- Copy paths EXACTLY from the findings - do not shorten or modify them\n- Only include files that were actually found in searches\n- Include the relevant class/function names within each file\n- Don't invent file paths that weren't in the findings\n\nExample of CORRECT file_path: \"src/core/handlers/base.py\"\nExample of WRONG file_path: \"base.py\" "
},
{
...
```
## Step 121: log (+17.4s)
**message:**
```
Gemini call took 2827ms
```
## Step 122: llm_response (+17.4s)
**response_format:**
```
FinalAnswer
```
**result:**
```
{
"summary": "The `apply_scene_seed` function is defined in `infinigen/core/__init__.py`. However, the provided search results do not show this function directly setting the numpy random seed. The `find_config` method, also in `infinigen/core/__init__.py`, is the only item that appears in the search results related to configuration, but it is not directly linked to setting the numpy seed within `apply_scene_seed`.",
"code_locations": [
{
"file_path": "infinigen/core/__init__.py",
"relevant_elements": [
"apply_scene_seed",
"find_config"
],
"line_range": null,
"relevance": ""
}
],
"reasoning_chain": [
"Searched for 'apply_scene_seed' function.",
"Found 'apply_scene_seed' in 'infinigen/core/__init__.py'.",
"Examined 'infinigen/core/__init__.py' for numpy random seed setting within 'apply_scene_seed'.",
"Did not find direct numpy random seed setting within 'apply_scene_seed'.",
"Found 'find_config' in 'infini
...
```
## Step 123: log (+17.4s)
**message:**
```
Summary: The `apply_scene_seed` function is defined in `infinigen/core/__init__.py`. However, the provided se...
```
## Step 124: log (+17.4s)
**message:**
```
Code locations: 1
```
## Step 125: log (+17.4s)
**message:**
```
Confidence: low
```
## Step 126: log (+17.4s)
**message:**
```
[Tool] read_file: infinigen/core/__init__.py
```
## Step 127: log (+17.4s)
**message:**
```
[Tool] read_file: infinigen/core/__init__.py
```
## Step 128: log (+17.4s)
**message:**
```
[Tool] (cache hit)
```
## Step 129: log (+17.4s)
**message:**
```
Search complete:
```
## Step 130: log (+17.4s)
**message:**
```
Items found: 1
```
## Step 131: log (+17.4s)
**message:**
```
Total iterations: 4
```
## Step 132: log (+17.4s)
**message:**
```
Total time: 17347ms
```
## Step 133: log (+17.4s)
**message:**
```
LLM time: 13390ms
```
## Step 134: log (+17.4s)
**message:**
```
Tool time: 3957ms
```
## Step 135: log (+17.4s)
**message:**
```
Tools used: {'grep': 3, 'read_file': 1}
```
## Step 136: log (+17.4s)
**message:**
```
Confidence progression: low → low → low → high
```
## Step 137: log (+17.4s)
**message:**
```
High confidence reached at iteration: 4
```
## Step 138: final_result (+17.4s)
**found_files:**
```
[
"infinigen/core/__init__.py"
]
```
**patterns_used:**
```
[
"def apply_scene_seed",
"{'file_path': 'infinigen/core/__init__.py'}",
"numpy.random.seed",
"numpy.random.seed"
]
```
**total_time_ms:**
```
17347.189903259277
```
**error:**
```
None
```
