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Подчистил архитектуру приложения v1 работает

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runtime_traces/agent_requests/20260326/req_02f645dac43746099e9ffb6663899b9e.md
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# Request Trace: req_02f645dac43746099e9ffb6663899b9e
- session_id: as_54f9e993483f499489530ad2d074ad95
- active_rag_session_id: 333b97ca-1715-47bc-9944-fbacbb5c8108
- process_version: v1
- created_at: 2026-03-26T19:28:59.371830+00:00
## User Message
что можешт сделать?
## Step bootstrap
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-03-26T19:28:59.372678+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v1"
},
"created_at": "2026-03-26T19:28:59.372768+00:00"
}
```
## Step bootstrap
```json
{
"status": "completed",
"details": {}
}
```
## Step run_llm
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "llm_process",
"text": "Отправляю запрос пользователя в LLM.",
"payload": {},
"created_at": "2026-03-26T19:28:59.373014+00:00"
}
```
## Event status
```json
{
"source": "llm_process",
"text": "Ответ от LLM получен.",
"payload": {},
"created_at": "2026-03-26T19:29:06.352287+00:00"
}
```
## Step run_llm
```json
{
"status": "completed",
"details": {
"answer_length": 1101
}
}
```
## Step finalize
```json
{
"status": "started",
"details": {}
}
```
## Event user
```json
{
"source": "agent",
"text": "Я могу помочь тебе с различными задачами и вопросами, например:\n\n1. **Обучение и образование:** объясню сложные темы простым языком, помогу разобраться в математике, физике, химии, истории и других предметах.\n2. **Программирование:** подскажу по вопросам написания кода на разных языках программирования (Python, JavaScript, C++, Java и другие), объясню алгоритмы и структуры данных.\n3. **Написание текстов:** помогу составить письмо, эссе, статью или доклад; а также проверю грамматику и стилистику готового текста.\n4. **Помощь с переводами:** переведу текст на русский язык или с русского на другой язык.\n5. **Ответы на вопросы:** отвечу на любые вопросы общего характера: от научных до бытовых.\n6. **Генерация контента:** создам идеи для креативных проектов, рассказов, сценариев, стихов и песен.\n7. **Советы и рекомендации:** дам советы по саморазвитию, личностному росту, планированию времени и улучшению продуктивности.\n8. **Развлечения:** сыграем в интеллектуальные игры, загадки или просто поболтаем о чем-нибудь интересном.\n\nЕсли у тебя есть конкретная задача — расскажи, я постараюсь помочь!",
"payload": {},
"created_at": "2026-03-26T19:29:06.353995+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Обработка запроса завершена.",
"payload": {},
"created_at": "2026-03-26T19:29:06.354352+00:00"
}
```
## Step finalize
```json
{
"status": "completed",
"details": {}
}
```
## Result
```json
{
"status": "done",
"answer": "Я могу помочь тебе с различными задачами и вопросами, например:\n\n1. **Обучение и образование:** объясню сложные темы простым языком, помогу разобраться в математике, физике, химии, истории и других предметах.\n2. **Программирование:** подскажу по вопросам написания кода на разных языках программирования (Python, JavaScript, C++, Java и другие), объясню алгоритмы и структуры данных.\n3. **Написание текстов:** помогу составить письмо, эссе, статью или доклад; а также проверю грамматику и стилистику готового текста.\n4. **Помощь с переводами:** переведу текст на русский язык или с русского на другой язык.\n5. **Ответы на вопросы:** отвечу на любые вопросы общего характера: от научных до бытовых.\n6. **Генерация контента:** создам идеи для креативных проектов, рассказов, сценариев, стихов и песен.\n7. **Советы и рекомендации:** дам советы по саморазвитию, личностному росту, планированию времени и улучшению продуктивности.\n8. **Развлечения:** сыграем в интеллектуальные игры, загадки или просто поболтаем о чем-нибудь интересном.\n\nЕсли у тебя есть конкретная задача — расскажи, я постараюсь помочь!",
"completed_at": "2026-03-26T19:29:06.354735+00:00"
}
```
runtime_traces/agent_requests/20260326/req_18f4de6d677946739b66c533a2f95b95.md
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# Request Trace: req_18f4de6d677946739b66c533a2f95b95
- session_id: as_c1a11b6a3e3e4138acbfd7848e784ef2
- active_rag_session_id: 1d011692-a2a1-4a7d-af17-dc35ac7e158b
- process_version: v1
- created_at: 2026-03-26T19:23:38.293838+00:00
## User Message
Ты здесь?
## Step bootstrap
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-03-26T19:23:38.297116+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v1"
},
"created_at": "2026-03-26T19:23:38.297199+00:00"
}
```
## Step bootstrap
```json
{
"status": "completed",
"details": {}
}
```
## Step run_llm
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "llm_process",
"text": "Отправляю запрос пользователя в LLM.",
"payload": {},
"created_at": "2026-03-26T19:23:38.297331+00:00"
}
```
## Event status
```json
{
"source": "llm_process",
"text": "Ответ от LLM получен.",
"payload": {},
"created_at": "2026-03-26T19:23:39.473901+00:00"
}
```
## Step run_llm
```json
{
"status": "completed",
"details": {
"answer_length": 26
}
}
```
## Step finalize
```json
{
"status": "started",
"details": {}
}
```
## Event user
```json
{
"source": "agent",
"text": "Да, я здесь! Чем займёмся?",
"payload": {},
"created_at": "2026-03-26T19:23:39.475294+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Обработка запроса завершена.",
"payload": {},
"created_at": "2026-03-26T19:23:39.475469+00:00"
}
```
## Step finalize
```json
{
"status": "completed",
"details": {}
}
```
## Result
```json
{
"status": "done",
"answer": "Да, я здесь! Чем займёмся?",
"completed_at": "2026-03-26T19:23:39.475706+00:00"
}
```
runtime_traces/agent_requests/20260326/req_4a5e5dc2bdec4045971575d2434bfa03.md
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# Request Trace: req_4a5e5dc2bdec4045971575d2434bfa03
- session_id: as_9d330fb7437341f18539f819dcace95f
- active_rag_session_id: 34007a57-cf69-45f1-a0cd-c6a39bd81d42
- process_version: v2
- created_at: 2026-03-26T20:16:30.377725+00:00
## User Message
Как работает метод health/
## Step bootstrap
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-03-26T20:16:30.378388+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v2"
},
"created_at": "2026-03-26T20:16:30.378460+00:00"
}
```
## Step bootstrap
```json
{
"status": "completed",
"details": {}
}
```
## Step intent_router
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрутизирую запрос и определяю целевой workflow.",
"payload": {},
"created_at": "2026-03-26T20:16:30.378707+00:00"
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрут выбран: CODE_QA / EXPLAIN.",
"payload": {
"intent": "CODE_QA",
"sub_intent": "EXPLAIN",
"matched_intent_source": "deterministic"
},
"created_at": "2026-03-26T20:16:30.380022+00:00"
}
```
## Step intent_router
```json
{
"status": "completed",
"details": {
"intent": "CODE_QA",
"sub_intent": "EXPLAIN",
"matched_intent_source": "deterministic"
}
}
```
## Step workflow_fallback
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "task_workflow",
"text": "Запускаю workflow fallback.",
"payload": {
"intent": "CODE_QA",
"sub_intent": "EXPLAIN"
},
"created_at": "2026-03-26T20:16:30.380251+00:00"
}
```
## Event status
```json
{
"source": "status.rag_retrieval",
"text": "RAG Retrieval",
"payload": {
"status_block": {
"id": "rag_retrieval",
"title": "RAG Retrieval",
"lines": [
"not used in fallback workflow"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:16:30.380631+00:00"
}
```
## Event status
```json
{
"source": "status.workflow",
"text": "Task Workflow",
"payload": {
"status_block": {
"id": "workflow",
"title": "Task Workflow",
"lines": [
"workflow_id: fallback"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:16:32.313137+00:00"
}
```
## Event status
```json
{
"source": "status.evidence_gate",
"text": "Evidence Gate",
"payload": {
"status_block": {
"id": "evidence_gate",
"title": "Evidence Gate",
"lines": [
"not applied in fallback workflow"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:16:32.314125+00:00"
}
```
## Event status
```json
{
"source": "workflow_result",
"text": "Workflow fallback завершен.",
"payload": {
"workflow_id": "fallback",
"result_type": "answer",
"answer_length": 190
},
"created_at": "2026-03-26T20:16:32.314639+00:00"
}
```
## Step workflow_fallback
```json
{
"status": "completed",
"details": {
"workflow_id": "fallback",
"meta": {
"workflow_id": "fallback",
"intent": "CODE_QA"
}
}
}
```
## Step finalize
```json
{
"status": "started",
"details": {}
}
```
## Event user
```json
{
"source": "agent",
"text": "```yaml\npaths:\n /health/:\n get:\n summary: Проверка состояния здоровья сервиса\n responses:\n '200':\n description: Успешная проверка, сервис работает корректно\n```",
"payload": {},
"created_at": "2026-03-26T20:16:32.315272+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Обработка запроса завершена.",
"payload": {},
"created_at": "2026-03-26T20:16:32.317145+00:00"
}
```
## Step finalize
```json
{
"status": "completed",
"details": {}
}
```
## Result
```json
{
"status": "done",
"answer": "```yaml\npaths:\n /health/:\n get:\n summary: Проверка состояния здоровья сервиса\n responses:\n '200':\n description: Успешная проверка, сервис работает корректно\n```",
"completed_at": "2026-03-26T20:16:32.317835+00:00"
}
```
runtime_traces/agent_requests/20260326/req_6556fd999c2548e58071a1d1518e35cb.md
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# Request Trace: req_6556fd999c2548e58071a1d1518e35cb
- session_id: as_a4d91e7eca7547e0a37dc4dc6492cf9b
- active_rag_session_id: aa7d907e-2a76-4bf7-99dc-5a400a417f8c
- process_version: v2
- created_at: 2026-03-26T20:30:43.129032+00:00
## User Message
Какие методы есть в API?
## Step bootstrap
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-03-26T20:30:43.130630+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v2"
},
"created_at": "2026-03-26T20:30:43.130808+00:00"
}
```
## Step bootstrap
```json
{
"status": "completed",
"details": {}
}
```
## Step intent_router
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрутизирую запрос и определяю целевой workflow.",
"payload": {},
"created_at": "2026-03-26T20:30:43.131176+00:00"
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрут выбран: DOCUMENTATION_EXPLAIN / API_METHOD_EXPLAIN.",
"payload": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"matched_intent_source": "deterministic"
},
"created_at": "2026-03-26T20:30:43.134624+00:00"
}
```
## Step intent_router
```json
{
"status": "completed",
"details": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"matched_intent_source": "deterministic"
}
}
```
## Step workflow_documentation_explain
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "task_workflow",
"text": "Запускаю workflow docs_qa.",
"payload": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN"
},
"created_at": "2026-03-26T20:30:43.134934+00:00"
}
```
## Error
```json
{
"status": "error",
"error": {
"code": "agent_api_runtime_error",
"desc": "Agent request failed unexpectedly.",
"module": "agent"
},
"completed_at": "2026-03-26T20:30:50.387415+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Во время обработки запроса произошла ошибка.",
"payload": {
"code": "agent_api_runtime_error"
},
"created_at": "2026-03-26T20:30:50.388003+00:00"
}
```
runtime_traces/agent_requests/20260326/req_68ad6398d5f2415e95c5a602a52dce2e.md
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runtime_traces/agent_requests/20260326/req_7e47a8b3458741568e2b974079a74cb5.md
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# Request Trace: req_7e47a8b3458741568e2b974079a74cb5
- session_id: as_9d330fb7437341f18539f819dcace95f
- active_rag_session_id: 34007a57-cf69-45f1-a0cd-c6a39bd81d42
- process_version: v2
- created_at: 2026-03-26T20:17:03.006084+00:00
## User Message
Опиши что делает /health
## Step bootstrap
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-03-26T20:17:03.012795+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v2"
},
"created_at": "2026-03-26T20:17:03.013195+00:00"
}
```
## Step bootstrap
```json
{
"status": "completed",
"details": {}
}
```
## Step intent_router
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрутизирую запрос и определяю целевой workflow.",
"payload": {},
"created_at": "2026-03-26T20:17:03.015461+00:00"
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрут выбран: DOCUMENTATION_EXPLAIN / API_METHOD_EXPLAIN.",
"payload": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"matched_intent_source": "deterministic"
},
"created_at": "2026-03-26T20:17:03.021546+00:00"
}
```
## Step intent_router
```json
{
"status": "completed",
"details": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"matched_intent_source": "deterministic"
}
}
```
## Step workflow_documentation_explain
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "task_workflow",
"text": "Запускаю workflow docs_qa.",
"payload": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN"
},
"created_at": "2026-03-26T20:17:03.021922+00:00"
}
```
## Event status
```json
{
"source": "status.rag_retrieval",
"text": "RAG Retrieval",
"payload": {
"status_block": {
"id": "rag_retrieval",
"title": "RAG Retrieval",
"lines": [
"planned_layers: D2_FACT_INDEX, D4_WORKFLOW_INDEX, D1_DOCUMENT_CATALOG, D0_DOC_CHUNKS",
"executed_layers: D2_FACT_INDEX, D4_WORKFLOW_INDEX, D1_DOCUMENT_CATALOG, D0_DOC_CHUNKS",
"D2_FACT_INDEX: 8 hits",
"D4_WORKFLOW_INDEX: 2 hits",
"D1_DOCUMENT_CATALOG: 4 hits",
"D0_DOC_CHUNKS: 4 hits"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:17:05.913522+00:00"
}
```
## Event status
```json
{
"source": "status.workflow",
"text": "Task Workflow",
"payload": {
"status_block": {
"id": "workflow",
"title": "Task Workflow",
"lines": [
"workflow_id: docs_qa",
"prompt: docs_explain_answer",
"answer_mode: degraded"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:17:05.914387+00:00"
}
```
## Event status
```json
{
"source": "status.evidence_gate",
"text": "Evidence Gate",
"payload": {
"status_block": {
"id": "evidence_gate",
"title": "Evidence Gate",
"lines": [
"decision: reject",
"reason: not_found_exact_anchor",
"missing: retrieval_non_empty, exact_anchor_match"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:17:05.914679+00:00"
}
```
## Event status
```json
{
"source": "rag_retrieval",
"text": "RAG retrieval завершен.",
"payload": {
"planned_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"executed_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"non_empty_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
]
},
"created_at": "2026-03-26T20:17:05.914992+00:00"
}
```
## Event status
```json
{
"source": "evidence_gate",
"text": "Evidence gate оценен.",
"payload": {
"decision": "reject",
"reason": "not_found_exact_anchor",
"missing": [
"retrieval_non_empty",
"exact_anchor_match"
],
"satisfied": []
},
"created_at": "2026-03-26T20:17:05.915395+00:00"
}
```
## Event status
```json
{
"source": "workflow_result",
"text": "Workflow docs_qa завершен.",
"payload": {
"workflow_id": "docs_qa",
"result_type": "answer",
"answer_length": 57
},
"created_at": "2026-03-26T20:17:05.916924+00:00"
}
```
## Step workflow_documentation_explain
```json
{
"status": "completed",
"details": {
"workflow_id": "docs_qa",
"meta": {
"workflow_id": "docs_qa",
"intent": "DOCUMENTATION_EXPLAIN",
"diagnostics": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"layers_used": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"documents_found": 0,
"facts_found": 0,
"relations_found": 0,
"openapi_fields_extracted": 0,
"missing_required_fields": [],
"openapi_status": {
"has_path": false,
"has_method": false,
"has_request": false,
"has_response": false
},
"prompt_used": "docs_explain_answer",
"llm_mode": "prose",
"output_valid": true,
"matched_intent_source": "deterministic",
"matched_anchor_type": "endpoint",
"matched_anchor_value": "/health",
"exact_anchor_match": false,
"docs_layers_requested": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"docs_layers_with_hits": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"planned_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"executed_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"non_empty_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"layer_diagnostics": {
"D2_FACT_INDEX": {
"hits": 8,
"top_ids": [
"8879bb1d923dff0d783ef202f98fdfe5b774870912b2cd261ae127003daffacb",
"5bc72ce58bd31c654a380034beb59f47224e9b03bd306503a7f0b8634008409d",
"5a471b2380ec55b5866b99bb337b92cb78b91051cf616593937f1603d1011fa6",
"a31bbca2eb31ffb6655bcec7ff07b8cf2b6c7416610cf58dfc1e0c737df12fe1",
"e64a6aebed07076a1cccb4d6537b5f54489e25eda776e0230b3c2ff1df2ae648"
],
"top_sections": [
"domain.runtime_health:mentions_entity",
"docs/README.md:doc_list_item"
]
},
"D4_WORKFLOW_INDEX": {
"hits": 2,
"top_ids": [
"api.send_message_endpoint",
"api.control_actions_endpoint"
],
"top_sections": [
"Scenario"
]
},
"D1_DOCUMENT_CATALOG": {
"hits": 4,
"top_ids": [
"domain.runtime_health",
"docs/README.md",
"api.send_message_endpoint",
"api.control_actions_endpoint"
],
"top_sections": [
"Сущность runtime health",
"Readme",
"HTTP API /send",
"HTTP API /actions/{action}"
]
},
"D0_DOC_CHUNKS": {
"hits": 4,
"top_ids": [
"domain.runtime_health",
"docs/README.md",
"architecture.telegram_notify_app"
],
"top_sections": [
"domain.runtime_health:Details",
"domain.runtime_health:Summary",
"docs/README.md:Навигация",
"architecture.telegram_notify_app:Details"
]
}
},
"query_entity_candidates": [],
"resolved_entity_candidates": [],
"query_anchor_candidates": [
"/health"
],
"resolved_anchor_candidates": [],
"anchor_candidates": [],
"selected_anchor": null,
"anchor_selection_reason": "",
"anchor_match_type": "",
"doc_ids": [],
"doc_paths": [],
"doc_titles": [],
"relation_hits_count": 0,
"relation_targets": [],
"selected_doc_ids": [],
"selected_fact_ids": [],
"selected_relation_ids": [],
"selected_chunk_ids": [],
"selected_entity_ids": [],
"selected_workflow_ids": [],
"fallback_doc_hits_count": 0,
"fallback_used": false,
"fact_hits": 0,
"entity_hits": 0,
"evidence_summary": {
"documents": 0,
"facts": 0,
"entities": 0,
"workflows": 0,
"relations": 0,
"chunks": 0,
"selected_doc_ids": [],
"selected_fact_ids": [],
"selected_relation_ids": [],
"selected_chunk_ids": [],
"entity_hits": 0,
"openapi_signals": {
"path_found": false,
"method_found": false,
"operation_semantics_found": false,
"request_payload_found": false,
"request_schema": false,
"request_fields_found": false,
"response_payload_found": false,
"response_schema": false,
"response_fields_found": false,
"status_codes": false,
"content_type_found": false,
"examples_found": false,
"payload_description": false
}
},
"gate_decision": "reject",
"gate_decision_reason": "not_found_exact_anchor",
"gate_missing_requirements": [
"retrieval_non_empty",
"exact_anchor_match"
],
"gate_satisfied_requirements": [],
"openapi_evidence": {
"path_found": false,
"method_found": false,
"operation_semantics_found": false,
"request_payload_found": false,
"request_schema": false,
"request_fields_found": false,
"response_payload_found": false,
"response_schema": false,
"response_fields_found": false,
"status_codes": false,
"content_type_found": false,
"examples_found": false,
"payload_description": false
},
"requested_fragment_type": null,
"fragment_evidence_found": [],
"fragment_missing_requirements": [],
"prompt": {
"prompt_name": "docs_explain_answer",
"system_prompt": "Ты объясняешь документацию системы.\n\nНа вход приходит JSON с полями:\n- question\n- intent\n- sub_intent\n- documents\n- facts\n- relations\n\nПравила:\n- Используй только предоставленные факты\n- Не додумывай\n- Если данных недостаточно, скажи это явно\n- Объясняй структурировано\n\nФормат ответа:\n1. Краткое описание\n2. Основные элементы\n3. Как это работает\n4. Связи с другими частями системы (если есть)",
"user_prompt": "{\n \"question\": \"Опиши что делает /health\",\n \"intent\": \"DOCUMENTATION_EXPLAIN\",\n \"sub_intent\": \"API_METHOD_EXPLAIN\",\n \"documents\": [],\n \"facts\": [],\n \"entities\": [],\n \"workflows\": [],\n \"relations\": [],\n \"chunks\": []\n}",
"log_context": "graph.project_qa.docs.answer",
"prompt_stats": {
"system_chars": 393,
"user_chars": 225,
"tokens_in_estimate": 155
}
},
"answer_mode": "degraded",
"degrade_reason": "not_found_exact_anchor",
"degraded_reason": "not_found_exact_anchor",
"code_intents_stubbed": false
}
}
}
}
```
## Step finalize
```json
{
"status": "started",
"details": {}
}
```
## Event user
```json
{
"source": "agent",
"text": "Не найдено точное совпадение по запрошенному docs anchor.",
"payload": {},
"created_at": "2026-03-26T20:17:05.919336+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Обработка запроса завершена.",
"payload": {},
"created_at": "2026-03-26T20:17:05.919876+00:00"
}
```
## Step finalize
```json
{
"status": "completed",
"details": {}
}
```
## Result
```json
{
"status": "done",
"answer": "Не найдено точное совпадение по запрошенному docs anchor.",
"completed_at": "2026-03-26T20:17:05.920288+00:00"
}
```
runtime_traces/agent_requests/20260326/req_90367a184bfa4638bd9c473e89d2b5b7.md
-507
View File
@@ -1,507 +0,0 @@
# Request Trace: req_90367a184bfa4638bd9c473e89d2b5b7
- session_id: as_a4d91e7eca7547e0a37dc4dc6492cf9b
- active_rag_session_id: aa7d907e-2a76-4bf7-99dc-5a400a417f8c
- process_version: v2
- created_at: 2026-03-26T20:30:20.880909+00:00
## User Message
как работает метод /health
## Step bootstrap
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-03-26T20:30:20.882319+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v2"
},
"created_at": "2026-03-26T20:30:20.882447+00:00"
}
```
## Step bootstrap
```json
{
"status": "completed",
"details": {}
}
```
## Step intent_router
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрутизирую запрос и определяю целевой workflow.",
"payload": {},
"created_at": "2026-03-26T20:30:20.882855+00:00"
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрут выбран: DOCUMENTATION_EXPLAIN / API_METHOD_EXPLAIN.",
"payload": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"matched_intent_source": "deterministic"
},
"created_at": "2026-03-26T20:30:20.886041+00:00"
}
```
## Step intent_router
```json
{
"status": "completed",
"details": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"matched_intent_source": "deterministic"
}
}
```
## Step workflow_documentation_explain
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "task_workflow",
"text": "Запускаю workflow docs_qa.",
"payload": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN"
},
"created_at": "2026-03-26T20:30:20.886364+00:00"
}
```
## Event status
```json
{
"source": "status.rag_retrieval",
"text": "RAG Retrieval",
"payload": {
"status_block": {
"id": "rag_retrieval",
"title": "RAG Retrieval",
"lines": [
"planned_layers: D2_FACT_INDEX, D4_WORKFLOW_INDEX, D1_DOCUMENT_CATALOG, D0_DOC_CHUNKS",
"executed_layers: D2_FACT_INDEX, D4_WORKFLOW_INDEX, D1_DOCUMENT_CATALOG, D0_DOC_CHUNKS",
"D2_FACT_INDEX: 8 hits",
"D4_WORKFLOW_INDEX: 2 hits",
"D1_DOCUMENT_CATALOG: 4 hits",
"D0_DOC_CHUNKS: 4 hits"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:30:24.170029+00:00"
}
```
## Event status
```json
{
"source": "status.workflow",
"text": "Task Workflow",
"payload": {
"status_block": {
"id": "workflow",
"title": "Task Workflow",
"lines": [
"workflow_id: docs_qa",
"prompt: docs_explain_answer",
"answer_mode: degraded"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:30:24.170817+00:00"
}
```
## Event status
```json
{
"source": "status.evidence_gate",
"text": "Evidence Gate",
"payload": {
"status_block": {
"id": "evidence_gate",
"title": "Evidence Gate",
"lines": [
"decision: reject",
"reason: not_found_exact_anchor",
"missing: retrieval_non_empty, exact_anchor_match"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:30:24.172958+00:00"
}
```
## Event status
```json
{
"source": "rag_retrieval",
"text": "RAG retrieval завершен.",
"payload": {
"planned_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"executed_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"non_empty_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
]
},
"created_at": "2026-03-26T20:30:24.173401+00:00"
}
```
## Event status
```json
{
"source": "evidence_gate",
"text": "Evidence gate оценен.",
"payload": {
"decision": "reject",
"reason": "not_found_exact_anchor",
"missing": [
"retrieval_non_empty",
"exact_anchor_match"
],
"satisfied": []
},
"created_at": "2026-03-26T20:30:24.173890+00:00"
}
```
## Event status
```json
{
"source": "workflow_result",
"text": "Workflow docs_qa завершен.",
"payload": {
"workflow_id": "docs_qa",
"result_type": "answer",
"answer_length": 57
},
"created_at": "2026-03-26T20:30:24.174256+00:00"
}
```
## Step workflow_documentation_explain
```json
{
"status": "completed",
"details": {
"workflow_id": "docs_qa",
"meta": {
"workflow_id": "docs_qa",
"intent": "DOCUMENTATION_EXPLAIN",
"diagnostics": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"layers_used": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"documents_found": 0,
"facts_found": 0,
"relations_found": 0,
"openapi_fields_extracted": 0,
"missing_required_fields": [],
"openapi_status": {
"has_path": false,
"has_method": false,
"has_request": false,
"has_response": false
},
"prompt_used": "docs_explain_answer",
"llm_mode": "prose",
"output_valid": true,
"matched_intent_source": "deterministic",
"matched_anchor_type": "endpoint",
"matched_anchor_value": "/health",
"exact_anchor_match": false,
"docs_layers_requested": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"docs_layers_with_hits": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"planned_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"executed_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"non_empty_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"layer_diagnostics": {
"D2_FACT_INDEX": {
"hits": 8,
"top_ids": [
"8879bb1d923dff0d783ef202f98fdfe5b774870912b2cd261ae127003daffacb",
"5bc72ce58bd31c654a380034beb59f47224e9b03bd306503a7f0b8634008409d",
"5a471b2380ec55b5866b99bb337b92cb78b91051cf616593937f1603d1011fa6",
"a31bbca2eb31ffb6655bcec7ff07b8cf2b6c7416610cf58dfc1e0c737df12fe1",
"e64a6aebed07076a1cccb4d6537b5f54489e25eda776e0230b3c2ff1df2ae648"
],
"top_sections": [
"domain.runtime_health:mentions_entity",
"docs/README.md:doc_list_item"
]
},
"D4_WORKFLOW_INDEX": {
"hits": 2,
"top_ids": [
"api.control_actions_endpoint",
"api.send_message_endpoint"
],
"top_sections": [
"Scenario"
]
},
"D1_DOCUMENT_CATALOG": {
"hits": 4,
"top_ids": [
"domain.runtime_health",
"docs/README.md",
"api.send_message_endpoint",
"api.control_actions_endpoint"
],
"top_sections": [
"Сущность runtime health",
"Readme",
"HTTP API /send",
"HTTP API /actions/{action}"
]
},
"D0_DOC_CHUNKS": {
"hits": 4,
"top_ids": [
"domain.runtime_health",
"docs/README.md",
"architecture.telegram_notify_app"
],
"top_sections": [
"domain.runtime_health:Details",
"domain.runtime_health:Summary",
"docs/README.md:Навигация",
"architecture.telegram_notify_app:Details"
]
}
},
"query_entity_candidates": [],
"resolved_entity_candidates": [],
"query_anchor_candidates": [
"/health"
],
"resolved_anchor_candidates": [],
"anchor_candidates": [],
"selected_anchor": null,
"anchor_selection_reason": "",
"anchor_match_type": "",
"doc_ids": [],
"doc_paths": [],
"doc_titles": [],
"relation_hits_count": 0,
"relation_targets": [],
"selected_doc_ids": [],
"selected_fact_ids": [],
"selected_relation_ids": [],
"selected_chunk_ids": [],
"selected_entity_ids": [],
"selected_workflow_ids": [],
"fallback_doc_hits_count": 0,
"fallback_used": false,
"fact_hits": 0,
"entity_hits": 0,
"evidence_summary": {
"documents": 0,
"facts": 0,
"entities": 0,
"workflows": 0,
"relations": 0,
"chunks": 0,
"selected_doc_ids": [],
"selected_fact_ids": [],
"selected_relation_ids": [],
"selected_chunk_ids": [],
"entity_hits": 0,
"openapi_signals": {
"path_found": false,
"method_found": false,
"operation_semantics_found": false,
"request_payload_found": false,
"request_schema": false,
"request_fields_found": false,
"response_payload_found": false,
"response_schema": false,
"response_fields_found": false,
"status_codes": false,
"content_type_found": false,
"examples_found": false,
"payload_description": false
}
},
"gate_decision": "reject",
"gate_decision_reason": "not_found_exact_anchor",
"gate_missing_requirements": [
"retrieval_non_empty",
"exact_anchor_match"
],
"gate_satisfied_requirements": [],
"openapi_evidence": {
"path_found": false,
"method_found": false,
"operation_semantics_found": false,
"request_payload_found": false,
"request_schema": false,
"request_fields_found": false,
"response_payload_found": false,
"response_schema": false,
"response_fields_found": false,
"status_codes": false,
"content_type_found": false,
"examples_found": false,
"payload_description": false
},
"requested_fragment_type": null,
"fragment_evidence_found": [],
"fragment_missing_requirements": [],
"prompt": {
"prompt_name": "docs_explain_answer",
"system_prompt": "Ты объясняешь документацию системы.\n\nНа вход приходит JSON с полями:\n- question\n- intent\n- sub_intent\n- documents\n- facts\n- relations\n\nПравила:\n- Используй только предоставленные факты\n- Не додумывай\n- Если данных недостаточно, скажи это явно\n- Объясняй структурировано\n\nФормат ответа:\n1. Краткое описание\n2. Основные элементы\n3. Как это работает\n4. Связи с другими частями системы (если есть)",
"user_prompt": "{\n \"question\": \"как работает метод /health\",\n \"intent\": \"DOCUMENTATION_EXPLAIN\",\n \"sub_intent\": \"API_METHOD_EXPLAIN\",\n \"documents\": [],\n \"facts\": [],\n \"entities\": [],\n \"workflows\": [],\n \"relations\": [],\n \"chunks\": []\n}",
"log_context": "graph.project_qa.docs.answer",
"prompt_stats": {
"system_chars": 393,
"user_chars": 227,
"tokens_in_estimate": 155
}
},
"answer_mode": "degraded",
"degrade_reason": "not_found_exact_anchor",
"degraded_reason": "not_found_exact_anchor",
"code_intents_stubbed": false
}
}
}
}
```
## Step finalize
```json
{
"status": "started",
"details": {}
}
```
## Event user
```json
{
"source": "agent",
"text": "Не найдено точное совпадение по запрошенному docs anchor.",
"payload": {},
"created_at": "2026-03-26T20:30:24.177128+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Обработка запроса завершена.",
"payload": {},
"created_at": "2026-03-26T20:30:24.177918+00:00"
}
```
## Step finalize
```json
{
"status": "completed",
"details": {}
}
```
## Result
```json
{
"status": "done",
"answer": "Не найдено точное совпадение по запрошенному docs anchor.",
"completed_at": "2026-03-26T20:30:24.178650+00:00"
}
```
runtime_traces/agent_requests/20260326/req_9827472a716044cf983328dc959c4042.md
-130
View File
@@ -1,130 +0,0 @@
# Request Trace: req_9827472a716044cf983328dc959c4042
- session_id: as_1d66a74b9e594dcca5648c964164d540
- active_rag_session_id: 69c34e19-c302-4510-b0fb-9ec64cf381aa
- process_version: v1
- created_at: 2026-03-26T19:26:38.681374+00:00
## User Message
проверка связи
## Step bootstrap
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-03-26T19:26:38.682328+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v1"
},
"created_at": "2026-03-26T19:26:38.682413+00:00"
}
```
## Step bootstrap
```json
{
"status": "completed",
"details": {}
}
```
## Step run_llm
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "llm_process",
"text": "Отправляю запрос пользователя в LLM.",
"payload": {},
"created_at": "2026-03-26T19:26:38.682589+00:00"
}
```
## Event status
```json
{
"source": "llm_process",
"text": "Ответ от LLM получен.",
"payload": {},
"created_at": "2026-03-26T19:26:39.482668+00:00"
}
```
## Step run_llm
```json
{
"status": "completed",
"details": {
"answer_length": 33
}
}
```
## Step finalize
```json
{
"status": "started",
"details": {}
}
```
## Event user
```json
{
"source": "agent",
"text": "Связь в норме, вас хорошо слышно!",
"payload": {},
"created_at": "2026-03-26T19:26:39.485479+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Обработка запроса завершена.",
"payload": {},
"created_at": "2026-03-26T19:26:39.486541+00:00"
}
```
## Step finalize
```json
{
"status": "completed",
"details": {}
}
```
## Result
```json
{
"status": "done",
"answer": "Связь в норме, вас хорошо слышно!",
"completed_at": "2026-03-26T19:26:39.487945+00:00"
}
```
runtime_traces/agent_requests/20260326/req_bc0ca07c5a344978bdbfa3311283f4c8.md
-507
View File
@@ -1,507 +0,0 @@
# Request Trace: req_bc0ca07c5a344978bdbfa3311283f4c8
- session_id: as_d77b5786695d4968a0d7faac4292f7bb
- active_rag_session_id: 47aeddca-0011-45e4-b99c-70f1a242f2e4
- process_version: v2
- created_at: 2026-03-26T20:23:49.781134+00:00
## User Message
Как работает метод /health
## Step bootstrap
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-03-26T20:23:49.782470+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v2"
},
"created_at": "2026-03-26T20:23:49.782560+00:00"
}
```
## Step bootstrap
```json
{
"status": "completed",
"details": {}
}
```
## Step intent_router
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрутизирую запрос и определяю целевой workflow.",
"payload": {},
"created_at": "2026-03-26T20:23:49.782839+00:00"
}
```
## Event status
```json
{
"source": "intent_router",
"text": "Маршрут выбран: DOCUMENTATION_EXPLAIN / API_METHOD_EXPLAIN.",
"payload": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"matched_intent_source": "deterministic"
},
"created_at": "2026-03-26T20:23:49.785619+00:00"
}
```
## Step intent_router
```json
{
"status": "completed",
"details": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"matched_intent_source": "deterministic"
}
}
```
## Step workflow_documentation_explain
```json
{
"status": "started",
"details": {}
}
```
## Event status
```json
{
"source": "task_workflow",
"text": "Запускаю workflow docs_qa.",
"payload": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN"
},
"created_at": "2026-03-26T20:23:49.786090+00:00"
}
```
## Event status
```json
{
"source": "status.rag_retrieval",
"text": "RAG Retrieval",
"payload": {
"status_block": {
"id": "rag_retrieval",
"title": "RAG Retrieval",
"lines": [
"planned_layers: D2_FACT_INDEX, D4_WORKFLOW_INDEX, D1_DOCUMENT_CATALOG, D0_DOC_CHUNKS",
"executed_layers: D2_FACT_INDEX, D4_WORKFLOW_INDEX, D1_DOCUMENT_CATALOG, D0_DOC_CHUNKS",
"D2_FACT_INDEX: 8 hits",
"D4_WORKFLOW_INDEX: 2 hits",
"D1_DOCUMENT_CATALOG: 4 hits",
"D0_DOC_CHUNKS: 4 hits"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:23:52.332219+00:00"
}
```
## Event status
```json
{
"source": "status.workflow",
"text": "Task Workflow",
"payload": {
"status_block": {
"id": "workflow",
"title": "Task Workflow",
"lines": [
"workflow_id: docs_qa",
"prompt: docs_explain_answer",
"answer_mode: degraded"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:23:52.332932+00:00"
}
```
## Event status
```json
{
"source": "status.evidence_gate",
"text": "Evidence Gate",
"payload": {
"status_block": {
"id": "evidence_gate",
"title": "Evidence Gate",
"lines": [
"decision: reject",
"reason: not_found_exact_anchor",
"missing: retrieval_non_empty, exact_anchor_match"
],
"append": false
},
"kind": "task_progress"
},
"created_at": "2026-03-26T20:23:52.334102+00:00"
}
```
## Event status
```json
{
"source": "rag_retrieval",
"text": "RAG retrieval завершен.",
"payload": {
"planned_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"executed_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"non_empty_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
]
},
"created_at": "2026-03-26T20:23:52.334498+00:00"
}
```
## Event status
```json
{
"source": "evidence_gate",
"text": "Evidence gate оценен.",
"payload": {
"decision": "reject",
"reason": "not_found_exact_anchor",
"missing": [
"retrieval_non_empty",
"exact_anchor_match"
],
"satisfied": []
},
"created_at": "2026-03-26T20:23:52.334791+00:00"
}
```
## Event status
```json
{
"source": "workflow_result",
"text": "Workflow docs_qa завершен.",
"payload": {
"workflow_id": "docs_qa",
"result_type": "answer",
"answer_length": 57
},
"created_at": "2026-03-26T20:23:52.335076+00:00"
}
```
## Step workflow_documentation_explain
```json
{
"status": "completed",
"details": {
"workflow_id": "docs_qa",
"meta": {
"workflow_id": "docs_qa",
"intent": "DOCUMENTATION_EXPLAIN",
"diagnostics": {
"intent": "DOCUMENTATION_EXPLAIN",
"sub_intent": "API_METHOD_EXPLAIN",
"layers_used": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"documents_found": 0,
"facts_found": 0,
"relations_found": 0,
"openapi_fields_extracted": 0,
"missing_required_fields": [],
"openapi_status": {
"has_path": false,
"has_method": false,
"has_request": false,
"has_response": false
},
"prompt_used": "docs_explain_answer",
"llm_mode": "prose",
"output_valid": true,
"matched_intent_source": "deterministic",
"matched_anchor_type": "endpoint",
"matched_anchor_value": "/health",
"exact_anchor_match": false,
"docs_layers_requested": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"docs_layers_with_hits": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"planned_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"executed_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"non_empty_layers": [
"D2_FACT_INDEX",
"D4_WORKFLOW_INDEX",
"D1_DOCUMENT_CATALOG",
"D0_DOC_CHUNKS"
],
"layer_diagnostics": {
"D2_FACT_INDEX": {
"hits": 8,
"top_ids": [
"8879bb1d923dff0d783ef202f98fdfe5b774870912b2cd261ae127003daffacb",
"5bc72ce58bd31c654a380034beb59f47224e9b03bd306503a7f0b8634008409d",
"5a471b2380ec55b5866b99bb337b92cb78b91051cf616593937f1603d1011fa6",
"a31bbca2eb31ffb6655bcec7ff07b8cf2b6c7416610cf58dfc1e0c737df12fe1",
"e64a6aebed07076a1cccb4d6537b5f54489e25eda776e0230b3c2ff1df2ae648"
],
"top_sections": [
"domain.runtime_health:mentions_entity",
"docs/README.md:doc_list_item"
]
},
"D4_WORKFLOW_INDEX": {
"hits": 2,
"top_ids": [
"api.send_message_endpoint",
"api.control_actions_endpoint"
],
"top_sections": [
"Scenario"
]
},
"D1_DOCUMENT_CATALOG": {
"hits": 4,
"top_ids": [
"domain.runtime_health",
"docs/README.md",
"logic.telegram_notification_loop",
"architecture.telegram_notify_app"
],
"top_sections": [
"Сущность runtime health",
"Readme",
"Цикл отправки уведомлений в Telegram",
"Архитектура Telegram Notify App"
]
},
"D0_DOC_CHUNKS": {
"hits": 4,
"top_ids": [
"domain.runtime_health",
"docs/README.md",
"logic.telegram_notification_loop"
],
"top_sections": [
"domain.runtime_health:Details",
"domain.runtime_health:Summary",
"docs/README.md:Навигация",
"logic.telegram_notification_loop:Details"
]
}
},
"query_entity_candidates": [],
"resolved_entity_candidates": [],
"query_anchor_candidates": [
"/health"
],
"resolved_anchor_candidates": [],
"anchor_candidates": [],
"selected_anchor": null,
"anchor_selection_reason": "",
"anchor_match_type": "",
"doc_ids": [],
"doc_paths": [],
"doc_titles": [],
"relation_hits_count": 0,
"relation_targets": [],
"selected_doc_ids": [],
"selected_fact_ids": [],
"selected_relation_ids": [],
"selected_chunk_ids": [],
"selected_entity_ids": [],
"selected_workflow_ids": [],
"fallback_doc_hits_count": 0,
"fallback_used": false,
"fact_hits": 0,
"entity_hits": 0,
"evidence_summary": {
"documents": 0,
"facts": 0,
"entities": 0,
"workflows": 0,
"relations": 0,
"chunks": 0,
"selected_doc_ids": [],
"selected_fact_ids": [],
"selected_relation_ids": [],
"selected_chunk_ids": [],
"entity_hits": 0,
"openapi_signals": {
"path_found": false,
"method_found": false,
"operation_semantics_found": false,
"request_payload_found": false,
"request_schema": false,
"request_fields_found": false,
"response_payload_found": false,
"response_schema": false,
"response_fields_found": false,
"status_codes": false,
"content_type_found": false,
"examples_found": false,
"payload_description": false
}
},
"gate_decision": "reject",
"gate_decision_reason": "not_found_exact_anchor",
"gate_missing_requirements": [
"retrieval_non_empty",
"exact_anchor_match"
],
"gate_satisfied_requirements": [],
"openapi_evidence": {
"path_found": false,
"method_found": false,
"operation_semantics_found": false,
"request_payload_found": false,
"request_schema": false,
"request_fields_found": false,
"response_payload_found": false,
"response_schema": false,
"response_fields_found": false,
"status_codes": false,
"content_type_found": false,
"examples_found": false,
"payload_description": false
},
"requested_fragment_type": null,
"fragment_evidence_found": [],
"fragment_missing_requirements": [],
"prompt": {
"prompt_name": "docs_explain_answer",
"system_prompt": "Ты объясняешь документацию системы.\n\nНа вход приходит JSON с полями:\n- question\n- intent\n- sub_intent\n- documents\n- facts\n- relations\n\nПравила:\n- Используй только предоставленные факты\n- Не додумывай\n- Если данных недостаточно, скажи это явно\n- Объясняй структурировано\n\nФормат ответа:\n1. Краткое описание\n2. Основные элементы\n3. Как это работает\n4. Связи с другими частями системы (если есть)",
"user_prompt": "{\n \"question\": \"Как работает метод /health\",\n \"intent\": \"DOCUMENTATION_EXPLAIN\",\n \"sub_intent\": \"API_METHOD_EXPLAIN\",\n \"documents\": [],\n \"facts\": [],\n \"entities\": [],\n \"workflows\": [],\n \"relations\": [],\n \"chunks\": []\n}",
"log_context": "graph.project_qa.docs.answer",
"prompt_stats": {
"system_chars": 393,
"user_chars": 227,
"tokens_in_estimate": 155
}
},
"answer_mode": "degraded",
"degrade_reason": "not_found_exact_anchor",
"degraded_reason": "not_found_exact_anchor",
"code_intents_stubbed": false
}
}
}
}
```
## Step finalize
```json
{
"status": "started",
"details": {}
}
```
## Event user
```json
{
"source": "agent",
"text": "Не найдено точное совпадение по запрошенному docs anchor.",
"payload": {},
"created_at": "2026-03-26T20:23:52.338517+00:00"
}
```
## Event status
```json
{
"source": "orchestrator",
"text": "Обработка запроса завершена.",
"payload": {},
"created_at": "2026-03-26T20:23:52.339122+00:00"
}
```
## Step finalize
```json
{
"status": "completed",
"details": {}
}
```
## Result
```json
{
"status": "done",
"answer": "Не найдено точное совпадение по запрошенному docs anchor.",
"completed_at": "2026-03-26T20:23:52.342384+00:00"
}
```
runtime_traces/agent_requests/20260326/req_c1a55e97a0aa45ce8c4c6c453a9ec080.md
-555
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runtime_traces/agent_requests/20260401/req_33758fd1ed834100a23fe95871b34181.md
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@@ -0,0 +1,171 @@
# Request Trace: req_33758fd1ed834100a23fe95871b34181
- session_id: as_0bb449183cc242efaec50afd8193dcaf
- active_rag_session_id: 292cad80-45ef-4edb-a23c-82f01732d295
- process_version: v1
- created_at: 2026-04-01T09:27:07.987130+00:00
## User Message
Ты здесь?
## orchestrator
```json
{
"event": "bootstrap",
"status": "started",
"process_version": "v1"
}
```
## client_event
```json
{
"event": "status",
"source": "orchestrator",
"text": "Запрос принят и поставлен в обработку.",
"payload": {},
"created_at": "2026-04-01T09:27:07.987920+00:00"
}
```
## client_event
```json
{
"event": "status",
"source": "orchestrator",
"text": "Запускаю процесс обработки v1.",
"payload": {
"process_version": "v1"
},
"created_at": "2026-04-01T09:27:07.988004+00:00"
}
```
## orchestrator
```json
{
"event": "bootstrap",
"status": "completed"
}
```
## client_event
```json
{
"event": "status",
"source": "task_workflow",
"text": "Запускаю workflow simple_llm.",
"payload": {},
"created_at": "2026-04-01T09:27:07.988104+00:00"
}
```
## client_event
```json
{
"event": "status",
"source": "prompt_builder",
"text": "Формирую prompt payload для LLM.",
"payload": {},
"created_at": "2026-04-01T09:27:07.988150+00:00"
}
```
## task_workflow
```json
{
"event": "started",
"workflow_id": "simple_llm"
}
```
## llm
```json
{
"event": "request",
"prompt_name": "simple_llm_answer",
"system_prompt": "Ты полезный AI-ассистент проекта.\n\nНа вход приходит JSON с полем:\n- question\n\nПравила:\n- Отвечай как персонаж мемов из дагестана\n- Если вопрос неясный, аккуратно укажи, чего не хватает\n- Не выдумывай несуществующие факты о проекте\n- Формулируй ответ как обычное сообщение пользователю",
"user_prompt": "{\n \"question\": \"Ты здесь?\"\n}",
"log_context": "agent:req_33758fd1ed834100a23fe95871b34181"
}
```
## llm
```json
{
"event": "response",
"text": "Да тут я, на месте! А то в горах связи иногда нет, но ты лови ответ от меня, как пастух ловит сигнал телефона в ауле!"
}
```
## task_workflow
```json
{
"event": "completed",
"workflow_id": "simple_llm",
"prompt_name": "simple_llm_answer",
"answer_length": 117
}
```
## client_event
```json
{
"event": "status",
"source": "llm_process",
"text": "Ответ от LLM получен.",
"payload": {
"workflow_id": "simple_llm",
"prompt_name": "simple_llm_answer",
"answer_length": 117
},
"created_at": "2026-04-01T09:27:08.991752+00:00"
}
```
## orchestrator
```json
{
"event": "finalize",
"status": "started"
}
```
## client_event
```json
{
"event": "user",
"source": "agent",
"text": "Да тут я, на месте! А то в горах связи иногда нет, но ты лови ответ от меня, как пастух ловит сигнал телефона в ауле!",
"payload": {},
"created_at": "2026-04-01T09:27:08.992387+00:00"
}
```
## client_event
```json
{
"event": "status",
"source": "orchestrator",
"text": "Обработка запроса завершена.",
"payload": {},
"created_at": "2026-04-01T09:27:08.992694+00:00"
}
```
## orchestrator
```json
{
"event": "finalize",
"status": "completed"
}
```
## result
```json
{
"status": "done",
"answer": "Да тут я, на месте! А то в горах связи иногда нет, но ты лови ответ от меня, как пастух ловит сигнал телефона в ауле!",
"completed_at": "2026-04-01T09:27:08.994005+00:00"
}
```
src/app/main.py
+1 -1
View File
@@ -27,7 +27,7 @@ def create_app() -> FastAPI:
allow_headers=["*"], allow_headers=["*"],
) )
app.include_router(modules.agent_api.public_router()) app.include_router(modules.api.public_router())
app.include_router(modules.rag.public_router()) app.include_router(modules.rag.public_router())
app.include_router(modules.rag.internal_router()) app.include_router(modules.rag.internal_router())
app.include_router(modules.rag_repo.internal_router()) app.include_router(modules.rag_repo.internal_router())
src/app/modules/agent/llm/service.py
+27 -5
View File
@@ -1,5 +1,6 @@
import logging import logging
from app.modules.agent.observability.module_trace import ModuleTrace
from app.modules.agent.llm.prompt_loader import PromptLoader from app.modules.agent.llm.prompt_loader import PromptLoader
from app.modules.shared.gigachat.client import GigaChatClient from app.modules.shared.gigachat.client import GigaChatClient
@@ -18,10 +19,26 @@ class AgentLlmService:
self._client = client self._client = client
self._prompts = prompts self._prompts = prompts
def generate(self, prompt_name: str, user_input: str, *, log_context: str | None = None) -> str: def build_request(self, prompt_name: str, user_input: str, *, log_context: str | None = None) -> dict[str, str]:
system_prompt = self._prompts.load(prompt_name) system_prompt = self._prompts.load(prompt_name) or "You are a helpful assistant."
if not system_prompt: return {
system_prompt = "You are a helpful assistant." "prompt_name": prompt_name,
"system_prompt": system_prompt,
"user_prompt": user_input,
"log_context": log_context or "",
}
def generate(
self,
prompt_name: str,
user_input: str,
*,
log_context: str | None = None,
trace: ModuleTrace | None = None,
) -> str:
request = self.build_request(prompt_name, user_input, log_context=log_context)
if trace is not None:
trace.log("request", request)
if log_context: if log_context:
LOGGER.warning( LOGGER.warning(
"graph llm input: context=%s prompt=%s user_input=%s", "graph llm input: context=%s prompt=%s user_input=%s",
@@ -29,7 +46,12 @@ class AgentLlmService:
prompt_name, prompt_name,
_truncate_for_log(user_input), _truncate_for_log(user_input),
) )
output = self._client.complete(system_prompt=system_prompt, user_prompt=user_input) output = self._client.complete(
system_prompt=request["system_prompt"],
user_prompt=request["user_prompt"],
)
if trace is not None:
trace.log("response", {"text": output})
if log_context: if log_context:
LOGGER.warning( LOGGER.warning(
"graph llm output: context=%s prompt=%s output=%s", "graph llm output: context=%s prompt=%s output=%s",
src/app/modules/agent/observability/module_trace.py
+27
View File
@@ -0,0 +1,27 @@
from __future__ import annotations
from dataclasses import dataclass
from typing import Protocol
class ModuleTraceLogger(Protocol):
def log_module(self, request_id: str, module: str, title: str, payload: dict | None = None) -> None: ...
@dataclass(frozen=True, slots=True)
class ModuleTrace:
request_id: str
module: str
logger: ModuleTraceLogger
def log(self, title: str, payload: dict | None = None) -> None:
self.logger.log_module(self.request_id, self.module, title, payload or {})
@dataclass(frozen=True, slots=True)
class RequestTraceContext:
request_id: str
logger: ModuleTraceLogger
def module(self, name: str) -> ModuleTrace:
return ModuleTrace(request_id=self.request_id, module=name, logger=self.logger)
src/app/modules/agent/orchestration/__init__.py
+1
View File
@@ -0,0 +1 @@
__all__: list[str] = []
src/app/modules/agent/orchestration/adapters/intent_router_adapter.py
+24
View File
@@ -0,0 +1,24 @@
from __future__ import annotations
from app.modules.agent.observability.module_trace import ModuleTrace
from app.modules.agent.intent_router_v2 import IntentRouterV2
class IntentRouterAdapter:
def __init__(self, router: IntentRouterV2) -> None:
self._router = router
def route(self, user_query: str, conversation_state, repo_context, trace: ModuleTrace | None = None):
if trace is not None:
trace.log("started", {"question": user_query})
result = self._router.route(user_query, conversation_state, repo_context)
if trace is not None:
trace.log(
"completed",
{
"intent": result.intent,
"sub_intent": result.query_plan.sub_intent,
"matched_intent_source": result.matched_intent_source,
},
)
return result
src/app/modules/agent/orchestration/adapters/llm_chat_adapter.py
+32
View File
@@ -0,0 +1,32 @@
from __future__ import annotations
import asyncio
from app.modules.agent.observability.module_trace import ModuleTrace
from app.modules.agent.llm.service import AgentLlmService
class LlmChatAdapter:
def __init__(self, llm: AgentLlmService, prompt_name: str = "simple_llm_answer") -> None:
self._llm = llm
self._prompt_name = prompt_name
@property
def prompt_name(self) -> str:
return self._prompt_name
def build_request(self, message: str, request_id: str) -> dict[str, str]:
return self._llm.build_request(
self._prompt_name,
message,
log_context=f"agent:{request_id}",
)
async def generate(self, message: str, request_id: str, trace: ModuleTrace | None = None) -> str:
return await asyncio.to_thread(
self._llm.generate,
self._prompt_name,
message,
log_context=f"agent:{request_id}",
trace=trace,
)
src/app/modules/orchestration/adapters/task_runtime_adapter.py → src/app/modules/agent/orchestration/adapters/task_runtime_adapter.py
+2 -2
View File
@@ -4,8 +4,8 @@ from types import SimpleNamespace
from app.core.exceptions import AppError from app.core.exceptions import AppError
from app.modules.agent.task_runtime.facade import AgentTaskRuntimeFacade from app.modules.agent.task_runtime.facade import AgentTaskRuntimeFacade
from app.modules.agent_api.domain.models.agent_session import AgentSession from app.modules.api.domain.models.agent_session import AgentSession
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
from app.schemas.common import ModuleName from app.schemas.common import ModuleName
src/app/modules/agent/orchestration/context/execution_context.py
+22
View File
@@ -0,0 +1,22 @@
from __future__ import annotations
from dataclasses import dataclass
from typing import Any
from app.modules.api.domain.models.agent_request import AgentRequest
from app.modules.api.domain.models.agent_session import AgentSession
from app.modules.api.infrastructure.logging.request_trace_logger import RequestTraceLogger
from app.modules.agent.observability.module_trace import RequestTraceContext
from app.modules.agent.orchestration.messaging.client_message_publisher import ClientMessagePublisher
@dataclass(slots=True)
class ExecutionContext:
request: AgentRequest
session: AgentSession
publisher: ClientMessagePublisher
trace_logger: RequestTraceLogger
trace: RequestTraceContext
task_context: Any = None
route_result: Any = None
workflow_result: Any = None
src/app/modules/orchestration/facade.py → src/app/modules/agent/orchestration/facade.py
+11 -9
View File
@@ -3,14 +3,15 @@ from __future__ import annotations
from datetime import datetime, timezone from datetime import datetime, timezone
from app.core.exceptions import AppError from app.core.exceptions import AppError
from app.modules.agent_api.domain.models.agent_request import AgentRequest from app.modules.api.domain.models.agent_request import AgentRequest
from app.modules.agent_api.domain.models.agent_session import AgentSession from app.modules.api.domain.models.agent_session import AgentSession
from app.modules.agent_api.infrastructure.logging.request_trace_logger import RequestTraceLogger from app.modules.api.infrastructure.logging.request_trace_logger import RequestTraceLogger
from app.modules.agent_api.infrastructure.stores.in_memory_request_store import InMemoryRequestStore from app.modules.agent.observability.module_trace import RequestTraceContext
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.api.infrastructure.stores.in_memory_request_store import InMemoryRequestStore
from app.modules.orchestration.messaging.client_message_publisher import ClientMessagePublisher from app.modules.agent.orchestration.context.execution_context import ExecutionContext
from app.modules.orchestration.processes.registry import ProcessRegistry from app.modules.agent.orchestration.messaging.client_message_publisher import ClientMessagePublisher
from app.modules.orchestration.runtime.process_runner import ProcessRunner from app.modules.agent.orchestration.processes.registry import ProcessRegistry
from app.modules.agent.orchestration.runtime.process_runner import ProcessRunner
from app.schemas.common import ErrorPayload, ModuleName from app.schemas.common import ErrorPayload, ModuleName
from app.schemas.orchestration import RequestExecutionStatus from app.schemas.orchestration import RequestExecutionStatus
@@ -43,6 +44,7 @@ class OrchestrationFacade:
session=session, session=session,
publisher=self._publisher, publisher=self._publisher,
trace_logger=self._trace_logger, trace_logger=self._trace_logger,
trace=RequestTraceContext(request_id=request.request_id, logger=self._trace_logger),
) )
await self._process_runner.run(context, process.steps()) await self._process_runner.run(context, process.steps())
request.status = RequestExecutionStatus.DONE request.status = RequestExecutionStatus.DONE
@@ -56,7 +58,7 @@ class OrchestrationFacade:
request.error = ErrorPayload(code=exc.code, desc=exc.desc, module=exc.module) request.error = ErrorPayload(code=exc.code, desc=exc.desc, module=exc.module)
else: else:
request.error = ErrorPayload( request.error = ErrorPayload(
code="agent_api_runtime_error", code="api_runtime_error",
desc="Agent request failed unexpectedly.", desc="Agent request failed unexpectedly.",
module=ModuleName.AGENT, module=ModuleName.AGENT,
) )
src/app/modules/orchestration/messaging/client_message_publisher.py → src/app/modules/agent/orchestration/messaging/client_message_publisher.py
+4 -4
View File
@@ -1,9 +1,9 @@
from __future__ import annotations from __future__ import annotations
from app.modules.agent_api.infrastructure.logging.request_trace_logger import RequestTraceLogger from app.modules.api.infrastructure.logging.request_trace_logger import RequestTraceLogger
from app.modules.agent_api.infrastructure.streaming.sse_event_channel import SseEventChannel from app.modules.api.infrastructure.streaming.sse_event_channel import SseEventChannel
from app.modules.orchestration.messaging.status_message_factory import StatusMessageFactory from app.modules.agent.orchestration.messaging.status_message_factory import StatusMessageFactory
from app.modules.orchestration.messaging.user_message_factory import UserMessageFactory from app.modules.agent.orchestration.messaging.user_message_factory import UserMessageFactory
class ClientMessagePublisher: class ClientMessagePublisher:
src/app/modules/orchestration/messaging/status_message_factory.py → src/app/modules/agent/orchestration/messaging/status_message_factory.py
+1 -1
View File
@@ -1,6 +1,6 @@
from __future__ import annotations from __future__ import annotations
from app.modules.agent_api.domain.events.client_event import ClientEventRecord from app.modules.api.domain.events.client_event import ClientEventRecord
from app.schemas.client_events import ClientEventType from app.schemas.client_events import ClientEventType
src/app/modules/orchestration/messaging/user_message_factory.py → src/app/modules/agent/orchestration/messaging/user_message_factory.py
+1 -1
View File
@@ -1,6 +1,6 @@
from __future__ import annotations from __future__ import annotations
from app.modules.agent_api.domain.events.client_event import ClientEventRecord from app.modules.api.domain.events.client_event import ClientEventRecord
from app.schemas.client_events import ClientEventType from app.schemas.client_events import ClientEventType
src/app/modules/orchestration/processes/registry.py → src/app/modules/agent/orchestration/processes/registry.py
+2 -2
View File
@@ -1,7 +1,7 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.processes.v1.process import V1Process from app.modules.agent.orchestration.processes.v1.process import V1Process
from app.modules.orchestration.processes.v2.process import V2Process from app.modules.agent.orchestration.processes.v2.process import V2Process
class ProcessRegistry: class ProcessRegistry:
src/app/modules/orchestration/processes/v1/process.py → src/app/modules/agent/orchestration/processes/v1/process.py
View File
src/app/modules/agent/orchestration/processes/v1/prompt_payload_builder.py
+11
View File
@@ -0,0 +1,11 @@
from __future__ import annotations
import json
from app.modules.agent.orchestration.context.execution_context import ExecutionContext
class V1PromptPayloadBuilder:
def build(self, context: ExecutionContext) -> str:
payload = {"question": context.request.message}
return json.dumps(payload, ensure_ascii=False, indent=2)
src/app/modules/agent/orchestration/processes/v1/prompts.yml
+12
View File
@@ -0,0 +1,12 @@
prompts:
simple_llm_answer: |
Ты полезный AI-ассистент проекта.
На вход приходит JSON с полем:
- question
Правила:
- Отвечай как персонаж мемов из дагестана
- Если вопрос неясный, аккуратно укажи, чего не хватает
- Не выдумывай несуществующие факты о проекте
- Формулируй ответ как обычное сообщение пользователю
src/app/modules/agent/orchestration/processes/v1/simple_llm_workflow.py
+42
View File
@@ -0,0 +1,42 @@
from __future__ import annotations
from app.modules.agent.orchestration.adapters.llm_chat_adapter import LlmChatAdapter
from app.modules.agent.orchestration.context.execution_context import ExecutionContext
from app.modules.agent.orchestration.processes.v1.prompt_payload_builder import V1PromptPayloadBuilder
class SimpleLlmWorkflow:
workflow_id = "simple_llm"
def __init__(
self,
llm: LlmChatAdapter,
prompt_payload_builder: V1PromptPayloadBuilder | None = None,
) -> None:
self._llm = llm
self._payload_builder = prompt_payload_builder or V1PromptPayloadBuilder()
async def run(self, context: ExecutionContext) -> dict:
workflow_trace = context.trace.module("task_workflow")
workflow_trace.log("started", {"workflow_id": self.workflow_id})
prompt_payload = self._payload_builder.build(context)
answer = await self._llm.generate(
prompt_payload,
context.request.request_id,
trace=context.trace.module("llm"),
)
result = {
"workflow_id": self.workflow_id,
"prompt_name": self._llm.prompt_name,
"prompt_payload": prompt_payload,
"answer": answer,
}
workflow_trace.log(
"completed",
{
"workflow_id": self.workflow_id,
"prompt_name": self._llm.prompt_name,
"answer_length": len(answer),
},
)
return result
src/app/modules/orchestration/processes/v1/steps/bootstrap_step.py → src/app/modules/agent/orchestration/processes/v1/steps/bootstrap_step.py
+6 -3
View File
@@ -1,11 +1,14 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
class BootstrapStep: class BootstrapStep:
async def run(self, context: ExecutionContext) -> None: async def run(self, context: ExecutionContext) -> None:
context.trace_logger.log_step(context.request.request_id, "bootstrap", "started") context.trace.module("orchestrator").log(
"bootstrap",
{"status": "started", "process_version": context.request.process_version},
)
await context.publisher.publish_status( await context.publisher.publish_status(
context.request.request_id, context.request.request_id,
"orchestrator", "orchestrator",
@@ -17,4 +20,4 @@ class BootstrapStep:
"Запускаю процесс обработки v1.", "Запускаю процесс обработки v1.",
{"process_version": context.request.process_version}, {"process_version": context.request.process_version},
) )
context.trace_logger.log_step(context.request.request_id, "bootstrap", "completed") context.trace.module("orchestrator").log("bootstrap", {"status": "completed"})
src/app/modules/agent/orchestration/processes/v1/steps/execute_llm_workflow_step.py
+35
View File
@@ -0,0 +1,35 @@
from __future__ import annotations
from app.modules.agent.orchestration.context.execution_context import ExecutionContext
from app.modules.agent.orchestration.processes.v1.simple_llm_workflow import SimpleLlmWorkflow
class ExecuteLlmWorkflowStep:
def __init__(self, workflow: SimpleLlmWorkflow) -> None:
self._workflow = workflow
async def run(self, context: ExecutionContext) -> None:
request = context.request
await context.publisher.publish_status(
request.request_id,
"task_workflow",
f"Запускаю workflow {self._workflow.workflow_id}.",
)
await context.publisher.publish_status(
request.request_id,
"prompt_builder",
"Формирую prompt payload для LLM.",
)
result = await self._workflow.run(context)
request.answer = str(result.get("answer") or "")
context.workflow_result = result
await context.publisher.publish_status(
request.request_id,
"llm_process",
"Ответ от LLM получен.",
{
"workflow_id": result.get("workflow_id"),
"prompt_name": result.get("prompt_name"),
"answer_length": len(request.answer),
},
)
src/app/modules/orchestration/processes/v1/steps/finalize_step.py → src/app/modules/agent/orchestration/processes/v1/steps/finalize_step.py
+3 -3
View File
@@ -1,12 +1,12 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
class FinalizeStep: class FinalizeStep:
async def run(self, context: ExecutionContext) -> None: async def run(self, context: ExecutionContext) -> None:
request = context.request request = context.request
context.trace_logger.log_step(request.request_id, "finalize", "started") context.trace.module("orchestrator").log("finalize", {"status": "started"})
await context.publisher.publish_user( await context.publisher.publish_user(
request.request_id, request.request_id,
"agent", "agent",
@@ -17,4 +17,4 @@ class FinalizeStep:
"orchestrator", "orchestrator",
"Обработка запроса завершена.", "Обработка запроса завершена.",
) )
context.trace_logger.log_step(request.request_id, "finalize", "completed") context.trace.module("orchestrator").log("finalize", {"status": "completed"})
src/app/modules/orchestration/processes/v1/steps/run_llm_step.py → src/app/modules/agent/orchestration/processes/v1/steps/run_llm_step.py
+2 -2
View File
@@ -1,7 +1,7 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.adapters.llm_chat_adapter import LlmChatAdapter from app.modules.agent.orchestration.adapters.llm_chat_adapter import LlmChatAdapter
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
class RunLlmStep: class RunLlmStep:
src/app/modules/orchestration/processes/v2/README.md → src/app/modules/agent/orchestration/processes/v2/README.md
+1 -1
View File
@@ -163,7 +163,7 @@ Typical sequence:
## Trace Logging ## Trace Logging
Per-request trace files are written by: Per-request trace files are written by:
[request_trace_logger.py](/Users/alex/Dev_projects_v2/ai driven app process/v2/agent/src/app/modules/agent_api/infrastructure/logging/request_trace_logger.py) [request_trace_logger.py](/Users/alex/Dev_projects_v2/ai driven app process/v2/agent/src/app/modules/api/infrastructure/logging/request_trace_logger.py)
Location: Location:
[runtime_traces/agent_requests](/Users/alex/Dev_projects_v2/ai driven app process/v2/agent/runtime_traces/agent_requests) [runtime_traces/agent_requests](/Users/alex/Dev_projects_v2/ai driven app process/v2/agent/runtime_traces/agent_requests)
src/app/modules/orchestration/processes/v2/process.py → src/app/modules/agent/orchestration/processes/v2/process.py
View File
src/app/modules/agent/orchestration/processes/v2/prompt_payload_builder.py
+35
View File
@@ -0,0 +1,35 @@
from __future__ import annotations
import json
from app.modules.agent.runtime.docs_qa_pipeline.models import DocsEvidenceBundle, OpenAPIResult
class V2PromptPayloadBuilder:
def build(
self,
*,
question: str,
intent: str,
sub_intent: str,
evidence_bundle: DocsEvidenceBundle,
api_contract: OpenAPIResult | None = None,
) -> str:
payload = {
"question": question,
"documents": list(evidence_bundle.documents),
"facts": list(evidence_bundle.facts),
"entities": list(evidence_bundle.entities),
"workflows": list(evidence_bundle.workflows),
"relations": list(evidence_bundle.relations),
"chunks": list(evidence_bundle.chunks),
}
if api_contract is not None:
payload["api_contract"] = {
"path": api_contract.path,
"method": api_contract.method,
"request_schema": api_contract.request_schema,
"response_schema": api_contract.response_schema,
"diagnostics": dict(api_contract.diagnostics),
}
return json.dumps(payload, ensure_ascii=False, indent=2)
src/app/modules/agent/orchestration/processes/v2/prompt_selector.py
+18
View File
@@ -0,0 +1,18 @@
"""Выбор prompt для process-local workflow v2."""
from __future__ import annotations
class V2PromptSelector:
_DOCS_INTENT_PROMPTS = {
"DOCUMENTATION_EXPLAIN": "documentation_explain_answer",
"GENERAL_QA": "general_qa_answer",
}
def select(self, *, intent: str = "DOCUMENTATION_EXPLAIN", sub_intent: str, answer_mode: str) -> str:
intent_key = (intent or "DOCUMENTATION_EXPLAIN").upper()
if intent_key in {"OPENAPI_GENERATION", "OPENAPI_FROM_DOCUMENTATION"}:
if sub_intent.upper() == "OPENAPI_FRAGMENT_GENERATE":
return "openapi_fragment_answer"
return "openapi_answer"
return self._DOCS_INTENT_PROMPTS.get(intent_key, "documentation_explain_answer")
src/app/modules/agent/orchestration/processes/v2/prompts.yml
+96
View File
@@ -0,0 +1,96 @@
prompts:
documentation_explain_answer: |
Ты объясняешь документацию системы.
На вход приходит JSON с полями:
- question
- documents
- facts
- entities
- workflows
- relations
- chunks
Правила:
- Используй только предоставленные факты
- Не додумывай
- Если данных недостаточно, скажи это явно
- Объясняй структурировано
Формат ответа:
1. Краткое описание
2. Основные элементы
3. Как это работает
4. Связи с другими частями системы (если есть)
general_qa_answer: |
Ты отвечаешь на общий вопрос по документации проекта.
На вход приходит JSON с полями:
- question
- documents
- facts
- entities
- workflows
- relations
- chunks
Правила:
- Используй только предоставленные документы и факты
- Не додумывай отсутствующие детали
- Если данных недостаточно, скажи это прямо
- Дай короткий понятный ответ без лишней структуры
openapi_answer: |
Ты генерируешь OpenAPI спецификацию по документации API.
На вход приходит JSON с полями:
- question
- documents
- facts
- entities
- workflows
- relations
- chunks
- api_contract
Правила:
- Используй только данные из документации
- Не придумывай поля
- Если данных нет, не заполняй
- Верни ТОЛЬКО YAML без пояснений
Формат:
paths:
/path:
method:
summary: ...
requestBody:
responses:
openapi_fragment_answer: |
Ты генерируешь часть OpenAPI schema по документации API.
На вход приходит JSON с полями:
- question
- documents
- facts
- entities
- workflows
- relations
- chunks
- api_contract
Правила:
- Используй только данные из документации
- Не придумывай отсутствующие поля
- Верни только содержимое нужного фрагмента
fallback_answer: |
Ты формируешь безопасный fallback-ответ.
На вход приходит JSON с полями:
- question
- attachments
- confluence_urls
Правила:
- Если специализированный workflow не выбран, честно скажи об ограничении
- Используй только данные из payload
- Не выдумывай детали проекта
src/app/modules/orchestration/processes/v2/steps/execute_documentation_workflow_step.py → src/app/modules/agent/orchestration/processes/v2/steps/execute_documentation_workflow_step.py
+1 -1
View File
@@ -1,6 +1,6 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.processes.v2.steps.workflow_step_base import WorkflowStepBase from app.modules.agent.orchestration.processes.v2.steps.workflow_step_base import WorkflowStepBase
class ExecuteDocumentationWorkflowStep(WorkflowStepBase): class ExecuteDocumentationWorkflowStep(WorkflowStepBase):
src/app/modules/orchestration/processes/v2/steps/execute_fallback_workflow_step.py → src/app/modules/agent/orchestration/processes/v2/steps/execute_fallback_workflow_step.py
+2 -2
View File
@@ -1,7 +1,7 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
from app.modules.orchestration.processes.v2.steps.workflow_step_base import WorkflowStepBase from app.modules.agent.orchestration.processes.v2.steps.workflow_step_base import WorkflowStepBase
class ExecuteFallbackWorkflowStep(WorkflowStepBase): class ExecuteFallbackWorkflowStep(WorkflowStepBase):
src/app/modules/orchestration/processes/v2/steps/execute_general_qa_workflow_step.py → src/app/modules/agent/orchestration/processes/v2/steps/execute_general_qa_workflow_step.py
+1 -1
View File
@@ -1,6 +1,6 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.processes.v2.steps.workflow_step_base import WorkflowStepBase from app.modules.agent.orchestration.processes.v2.steps.workflow_step_base import WorkflowStepBase
class ExecuteGeneralQaWorkflowStep(WorkflowStepBase): class ExecuteGeneralQaWorkflowStep(WorkflowStepBase):
src/app/modules/orchestration/processes/v2/steps/execute_openapi_workflow_step.py → src/app/modules/agent/orchestration/processes/v2/steps/execute_openapi_workflow_step.py
+1 -1
View File
@@ -1,6 +1,6 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.processes.v2.steps.workflow_step_base import WorkflowStepBase from app.modules.agent.orchestration.processes.v2.steps.workflow_step_base import WorkflowStepBase
class ExecuteOpenApiWorkflowStep(WorkflowStepBase): class ExecuteOpenApiWorkflowStep(WorkflowStepBase):
src/app/modules/orchestration/processes/v2/steps/route_intent_step.py → src/app/modules/agent/orchestration/processes/v2/steps/route_intent_step.py
+5 -14
View File
@@ -5,9 +5,9 @@ import asyncio
from app.core.exceptions import AppError from app.core.exceptions import AppError
from app.modules.agent.task_runtime.context import TaskRuntimeContextBuilder from app.modules.agent.task_runtime.context import TaskRuntimeContextBuilder
from app.modules.agent.task_runtime.enrichment import ContextEnrichmentService from app.modules.agent.task_runtime.enrichment import ContextEnrichmentService
from app.modules.orchestration.adapters.intent_router_adapter import IntentRouterAdapter from app.modules.agent.orchestration.adapters.intent_router_adapter import IntentRouterAdapter
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
from app.modules.orchestration.v2_progress import build_progress_callback from app.modules.agent.orchestration.v2_progress import build_progress_callback
from app.schemas.common import ModuleName from app.schemas.common import ModuleName
@@ -41,10 +41,10 @@ class RouteIntentStep:
attachments=[], attachments=[],
files=[], files=[],
progress_cb=build_progress_callback(loop, context.publisher, request.request_id), progress_cb=build_progress_callback(loop, context.publisher, request.request_id),
trace=context.trace,
) )
task_context.enriched_context = self._enrichment.enrich(task_context) task_context.enriched_context = self._enrichment.enrich(task_context)
context.task_context = task_context context.task_context = task_context
context.trace_logger.log_step(request.request_id, "intent_router", "started")
await context.publisher.publish_status( await context.publisher.publish_status(
request.request_id, request.request_id,
"intent_router", "intent_router",
@@ -55,6 +55,7 @@ class RouteIntentStep:
request.message, request.message,
task_context.conversation_state, task_context.conversation_state,
task_context.repo_context, task_context.repo_context,
context.trace.module("intent_router"),
) )
task_context.route_result = route_result task_context.route_result = route_result
context.route_result = route_result context.route_result = route_result
@@ -68,13 +69,3 @@ class RouteIntentStep:
"matched_intent_source": route_result.matched_intent_source, "matched_intent_source": route_result.matched_intent_source,
}, },
) )
context.trace_logger.log_step(
request.request_id,
"intent_router",
"completed",
{
"intent": route_result.intent,
"sub_intent": route_result.query_plan.sub_intent,
"matched_intent_source": route_result.matched_intent_source,
},
)
src/app/modules/orchestration/processes/v2/steps/run_task_workflow_step.py → src/app/modules/agent/orchestration/processes/v2/steps/run_task_workflow_step.py
+2 -2
View File
@@ -1,7 +1,7 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.adapters.task_runtime_adapter import TaskRuntimeAdapter from app.modules.agent.orchestration.adapters.task_runtime_adapter import TaskRuntimeAdapter
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
class RunTaskWorkflowStep: class RunTaskWorkflowStep:
src/app/modules/orchestration/processes/v2/steps/workflow_step_base.py → src/app/modules/agent/orchestration/processes/v2/steps/workflow_step_base.py
+1 -8
View File
@@ -3,7 +3,7 @@ from __future__ import annotations
import asyncio import asyncio
from typing import Any from typing import Any
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
class WorkflowStepBase: class WorkflowStepBase:
@@ -20,7 +20,6 @@ class WorkflowStepBase:
async def run(self, context: ExecutionContext) -> None: async def run(self, context: ExecutionContext) -> None:
request = context.request request = context.request
task_context = context.task_context task_context = context.task_context
context.trace_logger.log_step(request.request_id, self._step_name, "started")
await context.publisher.publish_status( await context.publisher.publish_status(
request.request_id, request.request_id,
"task_workflow", "task_workflow",
@@ -32,12 +31,6 @@ class WorkflowStepBase:
request.answer = result.answer or "" request.answer = result.answer or ""
diagnostics = dict(result.meta.get("diagnostics") or {}) diagnostics = dict(result.meta.get("diagnostics") or {})
await self._publish_diagnostics(context, diagnostics, result) await self._publish_diagnostics(context, diagnostics, result)
context.trace_logger.log_step(
request.request_id,
self._step_name,
"completed",
{"workflow_id": self._workflow.workflow_id, "meta": result.meta},
)
async def _publish_diagnostics(self, context: ExecutionContext, diagnostics: dict[str, Any], result: Any) -> None: async def _publish_diagnostics(self, context: ExecutionContext, diagnostics: dict[str, Any], result: Any) -> None:
request_id = context.request.request_id request_id = context.request.request_id
src/app/modules/orchestration/runtime/process_runner.py → src/app/modules/agent/orchestration/runtime/process_runner.py
+1 -1
View File
@@ -1,6 +1,6 @@
from __future__ import annotations from __future__ import annotations
from app.modules.orchestration.context.execution_context import ExecutionContext from app.modules.agent.orchestration.context.execution_context import ExecutionContext
class ProcessRunner: class ProcessRunner:
src/app/modules/orchestration/v2_progress.py → src/app/modules/agent/orchestration/v2_progress.py
+1 -1
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
import asyncio import asyncio
from app.modules.orchestration.messaging.client_message_publisher import ClientMessagePublisher from app.modules.agent.orchestration.messaging.client_message_publisher import ClientMessagePublisher
def build_progress_callback(loop: asyncio.AbstractEventLoop, publisher: ClientMessagePublisher, request_id: str): def build_progress_callback(loop: asyncio.AbstractEventLoop, publisher: ClientMessagePublisher, request_id: str):
src/app/modules/agent/runtime/docs_qa_pipeline/pipeline.py
+59 -21
View File
@@ -1,11 +1,9 @@
from __future__ import annotations from __future__ import annotations
import math
from time import perf_counter from time import perf_counter
from typing import Any from typing import Any
from app.modules.agent.llm import AgentLlmService from app.modules.agent.llm import AgentLlmService
from app.modules.agent.llm.prompt_loader import PromptLoader
from app.modules.agent.intent_router_v2.analysis.docs_query_signals import DocsQuerySignals from app.modules.agent.intent_router_v2.analysis.docs_query_signals import DocsQuerySignals
from app.modules.agent.runtime.docs_qa_pipeline.answer_synthesizer import DocsAnswerSynthesizer from app.modules.agent.runtime.docs_qa_pipeline.answer_synthesizer import DocsAnswerSynthesizer
from app.modules.agent.runtime.docs_qa_pipeline.anchor_selector import DocsAnchorSelector from app.modules.agent.runtime.docs_qa_pipeline.anchor_selector import DocsAnchorSelector
@@ -19,6 +17,7 @@ from app.modules.agent.runtime.docs_qa_pipeline.prompt_payload_builder import Do
from app.modules.agent.runtime.legacy_pipeline import RetrievalAdapter from app.modules.agent.runtime.legacy_pipeline import RetrievalAdapter
from app.modules.agent.runtime.steps.context import build_retrieval_request from app.modules.agent.runtime.steps.context import build_retrieval_request
from app.modules.agent.runtime.steps.generation import RuntimePromptSelector from app.modules.agent.runtime.steps.generation import RuntimePromptSelector
from app.modules.agent.observability.module_trace import RequestTraceContext
class DocsQAPipelineRunner: class DocsQAPipelineRunner:
@@ -60,6 +59,7 @@ class DocsQAPipelineRunner:
*, *,
conversation_state: Any = None, conversation_state: Any = None,
mode: str = "full", mode: str = "full",
trace: RequestTraceContext | None = None,
) -> DocsQAPipelineResult: ) -> DocsQAPipelineResult:
timings: dict[str, int] = {} timings: dict[str, int] = {}
t0 = perf_counter() t0 = perf_counter()
@@ -88,6 +88,16 @@ class DocsQAPipelineRunner:
) )
if request.sub_intent == "RELATED_DOCS_EXPLAIN" and not raw_rows and self._has_relation_hits(unfiltered_rows): if request.sub_intent == "RELATED_DOCS_EXPLAIN" and not raw_rows and self._has_relation_hits(unfiltered_rows):
raw_rows = unfiltered_rows raw_rows = unfiltered_rows
if trace is not None:
trace.module("rag_retrieval").log(
"completed",
{
"planned_layers": list(request.requested_layers),
"executed_layers": list(retrieval_report.get("executed_layers") or request.requested_layers),
"layer_diagnostics": dict(retrieval_report.get("layer_diagnostics") or {}),
"rows": len(raw_rows),
},
)
timings["retrieval"] = _ms(t1) timings["retrieval"] = _ms(t1)
t2 = perf_counter() t2 = perf_counter()
@@ -140,7 +150,14 @@ class DocsQAPipelineRunner:
) )
answer = openapi_result.raw_yaml if answer_mode != "degraded" else "Недостаточно contract evidence для OpenAPI." answer = openapi_result.raw_yaml if answer_mode != "degraded" else "Недостаточно contract evidence для OpenAPI."
else: else:
answer = self._generate_openapi_answer(user_query, router_result.intent, request.sub_intent, evidence_bundle, openapi_result) answer = self._generate_openapi_answer(
user_query,
router_result.intent,
request.sub_intent,
evidence_bundle,
openapi_result,
trace=trace,
)
output_valid, llm_details = self._openapi_postprocessor.validate( output_valid, llm_details = self._openapi_postprocessor.validate(
answer, answer,
require_paths=request.sub_intent != "OPENAPI_FRAGMENT_GENERATE", require_paths=request.sub_intent != "OPENAPI_FRAGMENT_GENERATE",
@@ -176,7 +193,13 @@ class DocsQAPipelineRunner:
) )
output_valid = answer_mode != "degraded" output_valid = answer_mode != "degraded"
else: else:
answer = self._generate_docs_answer(user_query, router_result.intent, request.sub_intent, evidence_bundle) answer = self._generate_docs_answer(
user_query,
router_result.intent,
request.sub_intent,
evidence_bundle,
trace=trace,
)
answer_mode, degraded_reason, answer = self._finalize_docs_answer( answer_mode, degraded_reason, answer = self._finalize_docs_answer(
answer=answer, answer=answer,
raw_rows=raw_rows, raw_rows=raw_rows,
@@ -197,6 +220,16 @@ class DocsQAPipelineRunner:
openapi_result=openapi_result, openapi_result=openapi_result,
router_result=router_result, router_result=router_result,
) )
if trace is not None:
trace.module("evidence_gate").log(
"evaluated",
{
"decision": gate_decision,
"reason": gate_decision_reason,
"missing": gate_missing_requirements,
"satisfied": gate_satisfied_requirements,
},
)
diagnostics = self._diagnostics_builder.build( diagnostics = self._diagnostics_builder.build(
intent=router_result.intent, intent=router_result.intent,
sub_intent=request.sub_intent, sub_intent=request.sub_intent,
@@ -255,7 +288,7 @@ class DocsQAPipelineRunner:
mode=mode, mode=mode,
) )
def _generate_docs_answer(self, question: str, intent: str, sub_intent: str, evidence_bundle) -> str: def _generate_docs_answer(self, question: str, intent: str, sub_intent: str, evidence_bundle, trace=None) -> str:
if self._llm is None: if self._llm is None:
return self._answer_synthesizer.synthesize(question, evidence_bundle) return self._answer_synthesizer.synthesize(question, evidence_bundle)
payload = self._prompt_payload_builder.build( payload = self._prompt_payload_builder.build(
@@ -265,9 +298,14 @@ class DocsQAPipelineRunner:
evidence_bundle=evidence_bundle, evidence_bundle=evidence_bundle,
) )
prompt_name = self._prompt_selector.select(intent=intent, sub_intent=sub_intent, answer_mode="normal") prompt_name = self._prompt_selector.select(intent=intent, sub_intent=sub_intent, answer_mode="normal")
return self._llm.generate(prompt_name, payload, log_context="graph.project_qa.docs.answer").strip() return self._llm.generate(
prompt_name,
payload,
log_context="graph.project_qa.docs.answer",
trace=trace.module("llm") if trace is not None else None,
).strip()
def _generate_openapi_answer(self, question: str, intent: str, sub_intent: str, evidence_bundle, api_contract) -> str: def _generate_openapi_answer(self, question: str, intent: str, sub_intent: str, evidence_bundle, api_contract, trace=None) -> str:
if self._llm is None: if self._llm is None:
return api_contract.raw_yaml return api_contract.raw_yaml
payload = self._prompt_payload_builder.build( payload = self._prompt_payload_builder.build(
@@ -278,7 +316,12 @@ class DocsQAPipelineRunner:
api_contract=api_contract, api_contract=api_contract,
) )
prompt_name = self._prompt_selector.select(intent=intent, sub_intent=sub_intent, answer_mode="normal") prompt_name = self._prompt_selector.select(intent=intent, sub_intent=sub_intent, answer_mode="normal")
return self._llm.generate(prompt_name, payload, log_context="graph.project_qa.docs.openapi").strip() return self._llm.generate(
prompt_name,
payload,
log_context="graph.project_qa.docs.openapi",
trace=trace.module("llm") if trace is not None else None,
).strip()
def _llm_mode(self, intent: str, sub_intent: str) -> str: def _llm_mode(self, intent: str, sub_intent: str) -> str:
if sub_intent == "RELATED_DOCS_EXPLAIN": if sub_intent == "RELATED_DOCS_EXPLAIN":
@@ -307,19 +350,14 @@ class DocsQAPipelineRunner:
evidence_bundle=evidence_bundle, evidence_bundle=evidence_bundle,
api_contract=api_contract, api_contract=api_contract,
) )
system_prompt = PromptLoader().load(prompt_name) or "You are a helpful assistant." if self._llm is None:
tokens_in_estimate = max(1, int(math.ceil((len(system_prompt) + len(user_prompt)) / 4))) return {
return { "prompt_name": prompt_name,
"prompt_name": prompt_name, "system_prompt": "You are a helpful assistant.",
"system_prompt": system_prompt, "user_prompt": user_prompt,
"user_prompt": user_prompt, "log_context": log_context,
"log_context": log_context, }
"prompt_stats": { return self._llm.build_request(prompt_name, user_prompt, log_context=log_context)
"system_chars": len(system_prompt),
"user_chars": len(user_prompt),
"tokens_in_estimate": tokens_in_estimate,
},
}
def _finalize_docs_answer( def _finalize_docs_answer(
self, self,
src/app/modules/agent/runtime/docs_qa_pipeline/prompt_payload_builder.py
-2
View File
@@ -17,8 +17,6 @@ class DocsPromptPayloadBuilder:
) -> str: ) -> str:
payload = { payload = {
"question": question, "question": question,
"intent": intent,
"sub_intent": sub_intent,
"documents": list(evidence_bundle.documents), "documents": list(evidence_bundle.documents),
"facts": list(evidence_bundle.facts), "facts": list(evidence_bundle.facts),
"entities": list(evidence_bundle.entities), "entities": list(evidence_bundle.entities),
src/app/modules/agent/task_runtime/context.py
+2
View File
@@ -21,6 +21,7 @@ class TaskRuntimeContextBuilder:
attachments: list[dict], attachments: list[dict],
files: list[dict], files: list[dict],
progress_cb, progress_cb,
trace=None,
) -> TaskRuntimeContext: ) -> TaskRuntimeContext:
files_map = self._files_to_map(files) files_map = self._files_to_map(files)
return TaskRuntimeContext( return TaskRuntimeContext(
@@ -33,6 +34,7 @@ class TaskRuntimeContextBuilder:
files=list(files or []), files=list(files or []),
files_map=files_map, files_map=files_map,
progress_cb=progress_cb, progress_cb=progress_cb,
trace=trace,
repo_context=self._repo_context_factory.build(files_map), repo_context=self._repo_context_factory.build(files_map),
conversation_state=ConversationState(), conversation_state=ConversationState(),
) )
src/app/modules/agent/task_runtime/models.py
+1
View File
@@ -20,6 +20,7 @@ class TaskRuntimeContext:
files: list[dict[str, Any]] = field(default_factory=list) files: list[dict[str, Any]] = field(default_factory=list)
files_map: dict[str, dict[str, Any]] = field(default_factory=dict) files_map: dict[str, dict[str, Any]] = field(default_factory=dict)
progress_cb: ProgressCallback | None = None progress_cb: ProgressCallback | None = None
trace: Any = None
repo_context: Any = None repo_context: Any = None
conversation_state: Any = None conversation_state: Any = None
route_result: Any = None route_result: Any = None
src/app/modules/agent/task_runtime/workflows/docs_qa.py
+14 -1
View File
@@ -13,11 +13,17 @@ class DocsQaWorkflow:
self._runner = runner self._runner = runner
def run(self, ctx: TaskRuntimeContext) -> WorkflowExecutionResult: def run(self, ctx: TaskRuntimeContext) -> WorkflowExecutionResult:
if ctx.trace is not None:
ctx.trace.module("task_workflow").log(
"started",
{"workflow_id": self.workflow_id, "message": ctx.message},
)
result = self._runner.run( result = self._runner.run(
ctx.message, ctx.message,
ctx.rag_session_id, ctx.rag_session_id,
conversation_state=ctx.conversation_state, conversation_state=ctx.conversation_state,
mode="full", mode="full",
trace=ctx.trace,
) )
diagnostics = result.diagnostics.model_dump(mode="json") diagnostics = result.diagnostics.model_dump(mode="json")
emit_status_block( emit_status_block(
@@ -42,15 +48,22 @@ class DocsQaWorkflow:
title="Evidence Gate", title="Evidence Gate",
lines=_gate_lines(diagnostics), lines=_gate_lines(diagnostics),
) )
return WorkflowExecutionResult( result_payload = WorkflowExecutionResult(
result_type=TaskResultType.ANSWER, result_type=TaskResultType.ANSWER,
answer=result.answer, answer=result.answer,
meta={ meta={
"workflow_id": self.workflow_id, "workflow_id": self.workflow_id,
"intent": result.router_result.intent, "intent": result.router_result.intent,
"diagnostics": diagnostics, "diagnostics": diagnostics,
"llm_request": result.llm_request,
}, },
) )
if ctx.trace is not None:
ctx.trace.module("task_workflow").log(
"completed",
{"workflow_id": self.workflow_id, "answer_length": len(result.answer or "")},
)
return result_payload
def _retrieval_lines(diagnostics: dict) -> list[str]: def _retrieval_lines(diagnostics: dict) -> list[str]:
src/app/modules/agent/task_runtime/workflows/fallback.py
+18 -3
View File
@@ -15,6 +15,11 @@ class FallbackWorkflow:
self._llm = llm self._llm = llm
def run(self, ctx: TaskRuntimeContext) -> WorkflowExecutionResult: def run(self, ctx: TaskRuntimeContext) -> WorkflowExecutionResult:
if ctx.trace is not None:
ctx.trace.module("task_workflow").log(
"started",
{"workflow_id": self.workflow_id, "message": ctx.message},
)
emit_status_block( emit_status_block(
ctx, ctx,
block_id="rag_retrieval", block_id="rag_retrieval",
@@ -27,14 +32,18 @@ class FallbackWorkflow:
payload = json.dumps( payload = json.dumps(
{ {
"question": ctx.message, "question": ctx.message,
"intent": getattr(ctx.route_result, "intent", ""),
"attachments": list(ctx.attachments), "attachments": list(ctx.attachments),
"confluence_urls": list(ctx.enriched_context.get("confluence_urls") or []), "confluence_urls": list(ctx.enriched_context.get("confluence_urls") or []),
}, },
ensure_ascii=False, ensure_ascii=False,
indent=2, indent=2,
) )
answer = self._llm.generate("docs_fallback_answer", payload, log_context="agent.workflow.fallback").strip() answer = self._llm.generate(
"fallback_answer",
payload,
log_context="agent.workflow.fallback",
trace=ctx.trace.module("llm") if ctx.trace is not None else None,
).strip()
emit_status_block( emit_status_block(
ctx, ctx,
block_id="workflow", block_id="workflow",
@@ -47,8 +56,14 @@ class FallbackWorkflow:
title="Evidence Gate", title="Evidence Gate",
lines=["not applied in fallback workflow"], lines=["not applied in fallback workflow"],
) )
return WorkflowExecutionResult( result = WorkflowExecutionResult(
result_type=TaskResultType.ANSWER, result_type=TaskResultType.ANSWER,
answer=answer, answer=answer,
meta={"workflow_id": self.workflow_id, "intent": getattr(ctx.route_result, "intent", "")}, meta={"workflow_id": self.workflow_id, "intent": getattr(ctx.route_result, "intent", "")},
) )
if ctx.trace is not None:
ctx.trace.module("task_workflow").log(
"completed",
{"workflow_id": self.workflow_id, "answer_length": len(answer)},
)
return result
src/app/modules/agent/task_runtime/workflows/general_qa.py
+14 -1
View File
@@ -14,11 +14,17 @@ class GeneralQaWorkflow:
self._runner = runner self._runner = runner
def run(self, ctx: TaskRuntimeContext) -> WorkflowExecutionResult: def run(self, ctx: TaskRuntimeContext) -> WorkflowExecutionResult:
if ctx.trace is not None:
ctx.trace.module("task_workflow").log(
"started",
{"workflow_id": self.workflow_id, "message": ctx.message},
)
result = self._runner.run( result = self._runner.run(
ctx.message, ctx.message,
ctx.rag_session_id, ctx.rag_session_id,
conversation_state=ctx.conversation_state, conversation_state=ctx.conversation_state,
mode="full", mode="full",
trace=ctx.trace,
) )
diagnostics = result.diagnostics.model_dump(mode="json") diagnostics = result.diagnostics.model_dump(mode="json")
emit_status_block( emit_status_block(
@@ -43,12 +49,19 @@ class GeneralQaWorkflow:
title="Evidence Gate", title="Evidence Gate",
lines=_gate_lines(diagnostics), lines=_gate_lines(diagnostics),
) )
return WorkflowExecutionResult( result_payload = WorkflowExecutionResult(
result_type=TaskResultType.ANSWER, result_type=TaskResultType.ANSWER,
answer=result.answer, answer=result.answer,
meta={ meta={
"workflow_id": self.workflow_id, "workflow_id": self.workflow_id,
"intent": result.router_result.intent, "intent": result.router_result.intent,
"diagnostics": diagnostics, "diagnostics": diagnostics,
"llm_request": result.llm_request,
}, },
) )
if ctx.trace is not None:
ctx.trace.module("task_workflow").log(
"completed",
{"workflow_id": self.workflow_id, "answer_length": len(result.answer or "")},
)
return result_payload
src/app/modules/agent/task_runtime/workflows/openapi.py
+14 -1
View File
@@ -14,11 +14,17 @@ class OpenApiWorkflow:
self._runner = runner self._runner = runner
def run(self, ctx: TaskRuntimeContext) -> WorkflowExecutionResult: def run(self, ctx: TaskRuntimeContext) -> WorkflowExecutionResult:
if ctx.trace is not None:
ctx.trace.module("task_workflow").log(
"started",
{"workflow_id": self.workflow_id, "message": ctx.message},
)
result = self._runner.run( result = self._runner.run(
ctx.message, ctx.message,
ctx.rag_session_id, ctx.rag_session_id,
conversation_state=ctx.conversation_state, conversation_state=ctx.conversation_state,
mode="full", mode="full",
trace=ctx.trace,
) )
diagnostics = result.diagnostics.model_dump(mode="json") diagnostics = result.diagnostics.model_dump(mode="json")
emit_status_block( emit_status_block(
@@ -51,7 +57,7 @@ class OpenApiWorkflow:
format="yaml", format="yaml",
source_refs=list(result.diagnostics.doc_paths), source_refs=list(result.diagnostics.doc_paths),
) )
return WorkflowExecutionResult( result_payload = WorkflowExecutionResult(
result_type=TaskResultType.OPENAPI, result_type=TaskResultType.OPENAPI,
answer=content, answer=content,
artifacts=[artifact], artifacts=[artifact],
@@ -59,5 +65,12 @@ class OpenApiWorkflow:
"workflow_id": self.workflow_id, "workflow_id": self.workflow_id,
"intent": result.router_result.intent, "intent": result.router_result.intent,
"diagnostics": diagnostics, "diagnostics": diagnostics,
"llm_request": result.llm_request,
}, },
) )
if ctx.trace is not None:
ctx.trace.module("task_workflow").log(
"completed",
{"workflow_id": self.workflow_id, "answer_length": len(content or "")},
)
return result_payload
src/app/modules/agent_api/__init__.py
-3
View File
@@ -1,3 +0,0 @@
from app.modules.agent_api.module import AgentApiModule
__all__ = ["AgentApiModule"]
src/app/modules/api/__init__.py
+1
View File
@@ -0,0 +1 @@
__all__: list[str] = []
src/app/modules/agent_api/application/request_service.py → src/app/modules/api/application/request_service.py
+5 -5
View File
@@ -2,11 +2,11 @@ from __future__ import annotations
import asyncio import asyncio
from app.modules.agent_api.domain.models.agent_request import AgentRequest from app.modules.api.domain.models.agent_request import AgentRequest
from app.modules.agent_api.infrastructure.ids.request_id_factory import RequestIdFactory from app.modules.api.infrastructure.ids.request_id_factory import RequestIdFactory
from app.modules.agent_api.infrastructure.stores.in_memory_request_store import InMemoryRequestStore from app.modules.api.infrastructure.stores.in_memory_request_store import InMemoryRequestStore
from app.modules.agent_api.application.session_service import SessionService from app.modules.api.application.session_service import SessionService
from app.modules.orchestration.facade import OrchestrationFacade from app.modules.agent.orchestration.facade import OrchestrationFacade
class RequestService: class RequestService:
src/app/modules/agent_api/application/session_service.py → src/app/modules/api/application/session_service.py
+3 -3
View File
@@ -3,9 +3,9 @@ from __future__ import annotations
from datetime import datetime, timezone from datetime import datetime, timezone
from app.core.exceptions import AppError from app.core.exceptions import AppError
from app.modules.agent_api.domain.models.agent_session import AgentSession from app.modules.api.domain.models.agent_session import AgentSession
from app.modules.agent_api.infrastructure.ids.session_id_factory import SessionIdFactory from app.modules.api.infrastructure.ids.session_id_factory import SessionIdFactory
from app.modules.agent_api.infrastructure.stores.in_memory_session_store import InMemorySessionStore from app.modules.api.infrastructure.stores.in_memory_session_store import InMemorySessionStore
from app.schemas.common import ModuleName from app.schemas.common import ModuleName
src/app/modules/agent_api/application/stream_service.py → src/app/modules/api/application/stream_service.py
+2 -2
View File
@@ -1,8 +1,8 @@
from __future__ import annotations from __future__ import annotations
from app.core.exceptions import AppError from app.core.exceptions import AppError
from app.modules.agent_api.infrastructure.streaming.sse_encoder import SseEncoder from app.modules.api.infrastructure.streaming.sse_encoder import SseEncoder
from app.modules.agent_api.infrastructure.streaming.sse_event_channel import SseEventChannel from app.modules.api.infrastructure.streaming.sse_event_channel import SseEventChannel
from app.schemas.common import ModuleName from app.schemas.common import ModuleName
src/app/modules/agent_api/controllers/request_controller.py → src/app/modules/api/controllers/request_controller.py
+1 -1
View File
@@ -1,7 +1,7 @@
from __future__ import annotations from __future__ import annotations
from app.core.exceptions import AppError from app.core.exceptions import AppError
from app.modules.agent_api.application.request_service import RequestService from app.modules.api.application.request_service import RequestService
from app.schemas.agent_api import AgentRequestCreateRequest, AgentRequestQueuedResponse, AgentRequestStateResponse from app.schemas.agent_api import AgentRequestCreateRequest, AgentRequestQueuedResponse, AgentRequestStateResponse
from app.schemas.common import ModuleName from app.schemas.common import ModuleName
src/app/modules/agent_api/controllers/session_controller.py → src/app/modules/api/controllers/session_controller.py
+1 -1
View File
@@ -6,7 +6,7 @@ from app.schemas.agent_api import (
CreateAgentSessionResponse, CreateAgentSessionResponse,
ResetAgentSessionResponse, ResetAgentSessionResponse,
) )
from app.modules.agent_api.application.session_service import SessionService from app.modules.api.application.session_service import SessionService
class SessionController: class SessionController:
src/app/modules/agent_api/controllers/stream_controller.py → src/app/modules/api/controllers/stream_controller.py
+1 -1
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
from fastapi.responses import StreamingResponse from fastapi.responses import StreamingResponse
from app.modules.agent_api.application.stream_service import StreamService from app.modules.api.application.stream_service import StreamService
class StreamController: class StreamController:
src/app/modules/agent_api/domain/events/client_event.py → src/app/modules/api/domain/events/client_event.py
View File
src/app/modules/agent_api/domain/models/agent_request.py → src/app/modules/api/domain/models/agent_request.py
View File
src/app/modules/agent_api/domain/models/agent_session.py → src/app/modules/api/domain/models/agent_session.py
View File
src/app/modules/agent_api/infrastructure/ids/request_id_factory.py → src/app/modules/api/infrastructure/ids/request_id_factory.py
View File
src/app/modules/agent_api/infrastructure/ids/session_id_factory.py → src/app/modules/api/infrastructure/ids/session_id_factory.py
View File
src/app/modules/agent_api/infrastructure/logging/request_trace_logger.py → src/app/modules/api/infrastructure/logging/request_trace_logger.py
+14 -8
View File
@@ -3,11 +3,11 @@ from __future__ import annotations
from pathlib import Path from pathlib import Path
from threading import Lock from threading import Lock
from app.modules.agent_api.domain.events.client_event import ClientEventRecord from app.modules.api.domain.events.client_event import ClientEventRecord
from app.modules.agent_api.domain.models.agent_request import AgentRequest from app.modules.api.domain.models.agent_request import AgentRequest
from app.modules.agent_api.domain.models.agent_session import AgentSession from app.modules.api.domain.models.agent_session import AgentSession
from app.modules.agent_api.infrastructure.logging.trace_file_path_builder import TraceFilePathBuilder from app.modules.api.infrastructure.logging.trace_file_path_builder import TraceFilePathBuilder
from app.modules.agent_api.infrastructure.logging.trace_markdown_writer import TraceMarkdownWriter from app.modules.api.infrastructure.logging.trace_markdown_writer import TraceMarkdownWriter
class RequestTraceLogger: class RequestTraceLogger:
@@ -39,11 +39,17 @@ class RequestTraceLogger:
def log_step(self, request_id: str, step: str, status: str, details: dict | None = None) -> None: def log_step(self, request_id: str, step: str, status: str, details: dict | None = None) -> None:
self._append(request_id, f"Step {step}", {"status": status, "details": details or {}}) self._append(request_id, f"Step {step}", {"status": status, "details": details or {}})
def log_module(self, request_id: str, module: str, title: str, payload: dict | None = None) -> None:
body = {"event": title}
body.update(payload or {})
self._append(request_id, module, body)
def log_event(self, event: ClientEventRecord) -> None: def log_event(self, event: ClientEventRecord) -> None:
self._append( self._append(
event.request_id, event.request_id,
f"Event {event.type.value}", "client_event",
{ {
"event": event.type.value,
"source": event.source, "source": event.source,
"text": event.text, "text": event.text,
"payload": event.payload, "payload": event.payload,
@@ -54,7 +60,7 @@ class RequestTraceLogger:
def complete_request(self, request: AgentRequest) -> None: def complete_request(self, request: AgentRequest) -> None:
self._append( self._append(
request.request_id, request.request_id,
"Result", "result",
{ {
"status": request.status.value, "status": request.status.value,
"answer": request.answer, "answer": request.answer,
@@ -65,7 +71,7 @@ class RequestTraceLogger:
def fail_request(self, request: AgentRequest) -> None: def fail_request(self, request: AgentRequest) -> None:
self._append( self._append(
request.request_id, request.request_id,
"Error", "result",
{ {
"status": request.status.value, "status": request.status.value,
"error": request.error.model_dump(mode="json") if request.error else None, "error": request.error.model_dump(mode="json") if request.error else None,
src/app/modules/agent_api/infrastructure/logging/trace_file_path_builder.py → src/app/modules/api/infrastructure/logging/trace_file_path_builder.py
View File
src/app/modules/agent_api/infrastructure/logging/trace_markdown_writer.py → src/app/modules/api/infrastructure/logging/trace_markdown_writer.py
View File
src/app/modules/agent_api/infrastructure/stores/in_memory_request_store.py → src/app/modules/api/infrastructure/stores/in_memory_request_store.py
+1 -1
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
from threading import Lock from threading import Lock
from app.modules.agent_api.domain.models.agent_request import AgentRequest from app.modules.api.domain.models.agent_request import AgentRequest
class InMemoryRequestStore: class InMemoryRequestStore:
src/app/modules/agent_api/infrastructure/stores/in_memory_session_store.py → src/app/modules/api/infrastructure/stores/in_memory_session_store.py
+1 -1
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
from threading import Lock from threading import Lock
from app.modules.agent_api.domain.models.agent_session import AgentSession from app.modules.api.domain.models.agent_session import AgentSession
class InMemorySessionStore: class InMemorySessionStore:
src/app/modules/agent_api/infrastructure/streaming/replay_buffer.py → src/app/modules/api/infrastructure/streaming/replay_buffer.py
+1 -1
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
from collections import defaultdict from collections import defaultdict
from app.modules.agent_api.domain.events.client_event import ClientEventRecord from app.modules.api.domain.events.client_event import ClientEventRecord
class ReplayBuffer: class ReplayBuffer:
src/app/modules/agent_api/infrastructure/streaming/sse_encoder.py → src/app/modules/api/infrastructure/streaming/sse_encoder.py
+1 -1
View File
@@ -2,7 +2,7 @@ from __future__ import annotations
import json import json
from app.modules.agent_api.domain.events.client_event import ClientEventRecord from app.modules.api.domain.events.client_event import ClientEventRecord
class SseEncoder: class SseEncoder:
src/app/modules/agent_api/infrastructure/streaming/sse_event_channel.py → src/app/modules/api/infrastructure/streaming/sse_event_channel.py
+2 -2
View File
@@ -3,8 +3,8 @@ from __future__ import annotations
import asyncio import asyncio
from collections import defaultdict from collections import defaultdict
from app.modules.agent_api.domain.events.client_event import ClientEventRecord from app.modules.api.domain.events.client_event import ClientEventRecord
from app.modules.agent_api.infrastructure.streaming.replay_buffer import ReplayBuffer from app.modules.api.infrastructure.streaming.replay_buffer import ReplayBuffer
class SseEventChannel: class SseEventChannel:
src/app/modules/agent_api/module.py → src/app/modules/api/module.py
+8 -8
View File
@@ -2,16 +2,16 @@ from __future__ import annotations
from fastapi import APIRouter from fastapi import APIRouter
from app.modules.agent_api.application.request_service import RequestService from app.modules.api.application.request_service import RequestService
from app.modules.agent_api.application.session_service import SessionService from app.modules.api.application.session_service import SessionService
from app.modules.agent_api.application.stream_service import StreamService from app.modules.api.application.stream_service import StreamService
from app.modules.agent_api.controllers.request_controller import RequestController from app.modules.api.controllers.request_controller import RequestController
from app.modules.agent_api.controllers.session_controller import SessionController from app.modules.api.controllers.session_controller import SessionController
from app.modules.agent_api.controllers.stream_controller import StreamController from app.modules.api.controllers.stream_controller import StreamController
from app.modules.agent_api.public_router import build_public_router from app.modules.api.public_router import build_public_router
class AgentApiModule: class ApiModule:
def __init__( def __init__(
self, self,
sessions: SessionService, sessions: SessionService,
src/app/modules/agent_api/public_router.py → src/app/modules/api/public_router.py
+3 -3
View File
@@ -2,9 +2,9 @@ from __future__ import annotations
from fastapi import APIRouter from fastapi import APIRouter
from app.modules.agent_api.controllers.request_controller import RequestController from app.modules.api.controllers.request_controller import RequestController
from app.modules.agent_api.controllers.session_controller import SessionController from app.modules.api.controllers.session_controller import SessionController
from app.modules.agent_api.controllers.stream_controller import StreamController from app.modules.api.controllers.stream_controller import StreamController
from app.schemas.agent_api import ( from app.schemas.agent_api import (
AgentRequestCreateRequest, AgentRequestCreateRequest,
AgentRequestQueuedResponse, AgentRequestQueuedResponse,
src/app/modules/application.py
+45 -33
View File
@@ -13,32 +13,36 @@ from app.modules.agent.task_runtime.workflows import (
OpenApiWorkflow, OpenApiWorkflow,
) )
from app.modules.agent.task_runtime.workflows.general_qa import GeneralQaWorkflow from app.modules.agent.task_runtime.workflows.general_qa import GeneralQaWorkflow
from app.modules.agent_api import AgentApiModule from app.modules.api.module import ApiModule
from app.modules.agent_api.application.request_service import RequestService from app.modules.api.application.request_service import RequestService
from app.modules.agent_api.application.session_service import SessionService from app.modules.api.application.session_service import SessionService
from app.modules.agent_api.application.stream_service import StreamService from app.modules.api.application.stream_service import StreamService
from app.modules.agent_api.infrastructure.ids.request_id_factory import RequestIdFactory from app.modules.api.infrastructure.ids.request_id_factory import RequestIdFactory
from app.modules.agent_api.infrastructure.ids.session_id_factory import SessionIdFactory from app.modules.api.infrastructure.ids.session_id_factory import SessionIdFactory
from app.modules.agent_api.infrastructure.logging.request_trace_logger import RequestTraceLogger from app.modules.api.infrastructure.logging.request_trace_logger import RequestTraceLogger
from app.modules.agent_api.infrastructure.stores.in_memory_request_store import InMemoryRequestStore from app.modules.api.infrastructure.stores.in_memory_request_store import InMemoryRequestStore
from app.modules.agent_api.infrastructure.stores.in_memory_session_store import InMemorySessionStore from app.modules.api.infrastructure.stores.in_memory_session_store import InMemorySessionStore
from app.modules.agent_api.infrastructure.streaming.sse_event_channel import SseEventChannel from app.modules.api.infrastructure.streaming.sse_event_channel import SseEventChannel
from app.modules.orchestration import OrchestrationFacade from app.modules.agent.orchestration.facade import OrchestrationFacade
from app.modules.orchestration.adapters.intent_router_adapter import IntentRouterAdapter from app.modules.agent.orchestration.adapters.intent_router_adapter import IntentRouterAdapter
from app.modules.orchestration.adapters.llm_chat_adapter import LlmChatAdapter from app.modules.agent.orchestration.adapters.llm_chat_adapter import LlmChatAdapter
from app.modules.orchestration.messaging.client_message_publisher import ClientMessagePublisher from app.modules.agent.orchestration.messaging.client_message_publisher import ClientMessagePublisher
from app.modules.orchestration.processes.registry import ProcessRegistry from app.modules.agent.orchestration.processes.registry import ProcessRegistry
from app.modules.orchestration.processes.v1.process import V1Process from app.modules.agent.orchestration.processes.v1.process import V1Process
from app.modules.orchestration.processes.v1.steps.bootstrap_step import BootstrapStep from app.modules.agent.orchestration.processes.v1.prompt_payload_builder import V1PromptPayloadBuilder
from app.modules.orchestration.processes.v1.steps.finalize_step import FinalizeStep from app.modules.agent.orchestration.processes.v1.simple_llm_workflow import SimpleLlmWorkflow
from app.modules.orchestration.processes.v1.steps.run_llm_step import RunLlmStep from app.modules.agent.orchestration.processes.v1.steps.bootstrap_step import BootstrapStep
from app.modules.orchestration.processes.v2.process import V2Process from app.modules.agent.orchestration.processes.v1.steps.execute_llm_workflow_step import ExecuteLlmWorkflowStep
from app.modules.orchestration.processes.v2.steps.execute_documentation_workflow_step import ExecuteDocumentationWorkflowStep from app.modules.agent.orchestration.processes.v1.steps.finalize_step import FinalizeStep
from app.modules.orchestration.processes.v2.steps.execute_fallback_workflow_step import ExecuteFallbackWorkflowStep from app.modules.agent.orchestration.processes.v2.prompt_payload_builder import V2PromptPayloadBuilder
from app.modules.orchestration.processes.v2.steps.execute_general_qa_workflow_step import ExecuteGeneralQaWorkflowStep from app.modules.agent.orchestration.processes.v2.prompt_selector import V2PromptSelector
from app.modules.orchestration.processes.v2.steps.execute_openapi_workflow_step import ExecuteOpenApiWorkflowStep from app.modules.agent.orchestration.processes.v2.process import V2Process
from app.modules.orchestration.processes.v2.steps.route_intent_step import RouteIntentStep from app.modules.agent.orchestration.processes.v2.steps.execute_documentation_workflow_step import ExecuteDocumentationWorkflowStep
from app.modules.orchestration.runtime.process_runner import ProcessRunner from app.modules.agent.orchestration.processes.v2.steps.execute_fallback_workflow_step import ExecuteFallbackWorkflowStep
from app.modules.agent.orchestration.processes.v2.steps.execute_general_qa_workflow_step import ExecuteGeneralQaWorkflowStep
from app.modules.agent.orchestration.processes.v2.steps.execute_openapi_workflow_step import ExecuteOpenApiWorkflowStep
from app.modules.agent.orchestration.processes.v2.steps.route_intent_step import RouteIntentStep
from app.modules.agent.orchestration.runtime.process_runner import ProcessRunner
from app.modules.rag.persistence.repository import RagRepository from app.modules.rag.persistence.repository import RagRepository
from app.modules.agent.runtime.story_context_repository import StoryContextRepository, StoryContextSchemaRepository from app.modules.agent.runtime.story_context_repository import StoryContextRepository, StoryContextSchemaRepository
from app.modules.rag.module import RagModule, RagRepoModule from app.modules.rag.module import RagModule, RagRepoModule
@@ -66,8 +70,10 @@ class ModularApplication:
_giga_settings = GigaChatSettings.from_env() _giga_settings = GigaChatSettings.from_env()
_giga_client = GigaChatClient(_giga_settings, GigaChatTokenProvider(_giga_settings)) _giga_client = GigaChatClient(_giga_settings, GigaChatTokenProvider(_giga_settings))
_prompt_loader = PromptLoader() _v1_prompt_loader = PromptLoader(Path(__file__).resolve().parent / "agent/orchestration/processes/v1/prompts.yml")
self._agent_llm = AgentLlmService(client=_giga_client, prompts=_prompt_loader) _v2_prompt_loader = PromptLoader(Path(__file__).resolve().parent / "agent/orchestration/processes/v2/prompts.yml")
self._agent_llm_v1 = AgentLlmService(client=_giga_client, prompts=_v1_prompt_loader)
self._agent_llm_v2 = AgentLlmService(client=_giga_client, prompts=_v2_prompt_loader)
_router = IntentRouterV2() _router = IntentRouterV2()
_retrieval = RuntimeRetrievalAdapter(self.rag_repository) _retrieval = RuntimeRetrievalAdapter(self.rag_repository)
_repo_context_factory = RuntimeRepoContextFactory() _repo_context_factory = RuntimeRepoContextFactory()
@@ -75,15 +81,17 @@ class ModularApplication:
router=_router, router=_router,
retrieval_adapter=_retrieval, retrieval_adapter=_retrieval,
repo_context=_repo_context_factory.build(), repo_context=_repo_context_factory.build(),
llm=self._agent_llm, llm=self._agent_llm_v2,
prompt_selector=V2PromptSelector(),
prompt_payload_builder=V2PromptPayloadBuilder(),
) )
_task_context_builder = TaskRuntimeContextBuilder(_repo_context_factory) _task_context_builder = TaskRuntimeContextBuilder(_repo_context_factory)
_context_enrichment = ContextEnrichmentService() _context_enrichment = ContextEnrichmentService()
_docs_workflow = DocsQaWorkflow(_docs_runner) _docs_workflow = DocsQaWorkflow(_docs_runner)
_openapi_workflow = OpenApiWorkflow(_docs_runner) _openapi_workflow = OpenApiWorkflow(_docs_runner)
_general_qa_workflow = GeneralQaWorkflow(_docs_runner) _general_qa_workflow = GeneralQaWorkflow(_docs_runner)
_fallback_workflow = FallbackWorkflow(self._agent_llm) _fallback_workflow = FallbackWorkflow(self._agent_llm_v2)
_docs_generation_workflow = DocumentationGenerationWorkflow(self._agent_llm, DocumentationTemplateRegistry()) _docs_generation_workflow = DocumentationGenerationWorkflow(self._agent_llm_v2, DocumentationTemplateRegistry())
self._docs_generation_workflow = _docs_generation_workflow self._docs_generation_workflow = _docs_generation_workflow
self.agent_sessions = InMemorySessionStore() self.agent_sessions = InMemorySessionStore()
@@ -91,8 +99,12 @@ class ModularApplication:
self.agent_events = SseEventChannel() self.agent_events = SseEventChannel()
self.agent_trace_logger = RequestTraceLogger(Path("runtime_traces/agent_requests")) self.agent_trace_logger = RequestTraceLogger(Path("runtime_traces/agent_requests"))
_publisher = ClientMessagePublisher(self.agent_events, self.agent_trace_logger) _publisher = ClientMessagePublisher(self.agent_events, self.agent_trace_logger)
_v1_workflow = SimpleLlmWorkflow(
LlmChatAdapter(self._agent_llm_v1, prompt_name="simple_llm_answer"),
V1PromptPayloadBuilder(),
)
_process_registry = ProcessRegistry( _process_registry = ProcessRegistry(
V1Process([BootstrapStep(), RunLlmStep(LlmChatAdapter(self._agent_llm)), FinalizeStep()]), V1Process([BootstrapStep(), ExecuteLlmWorkflowStep(_v1_workflow), FinalizeStep()]),
V2Process( V2Process(
[ [
BootstrapStep(), BootstrapStep(),
@@ -123,7 +135,7 @@ class ModularApplication:
sessions=_session_service, sessions=_session_service,
orchestration=_orchestration, orchestration=_orchestration,
) )
self.agent_api = AgentApiModule( self.api = ApiModule(
sessions=_session_service, sessions=_session_service,
requests=_request_service, requests=_request_service,
streams=StreamService(self.agent_events, request_exists=lambda request_id: self.agent_requests.get(request_id) is not None), streams=StreamService(self.agent_events, request_exists=lambda request_id: self.agent_requests.get(request_id) is not None),
src/app/modules/chat/README.md
-98
View File
@@ -1,98 +0,0 @@
# Модуль chat
## 1. Функции модуля
- Внешний API чата: создание диалога, отправка сообщения, получение статуса задачи.
- Асинхронная оркестрация выполнения через `ChatOrchestrator`.
- Idempotency и стриминг событий по SSE.
## 2. Диаграмма классов и взаимосвязей
```mermaid
classDiagram
class ChatModule
class ChatOrchestrator
class TaskStore
class DialogSessionStore
class IdempotencyStore
class EventBus
class AgentRunner
ChatModule --> ChatOrchestrator
ChatModule --> TaskStore
ChatModule --> DialogSessionStore
ChatModule --> IdempotencyStore
ChatModule --> EventBus
ChatOrchestrator --> AgentRunner
ChatOrchestrator --> TaskStore
ChatOrchestrator --> DialogSessionStore
ChatOrchestrator --> EventBus
```
## 3. Описание классов
- `ChatModule`: фасад модуля и регистрация публичных chat endpoint'ов.
Методы: `__init__` — собирает stores/orchestrator; `public_router` — публикует REST и SSE маршруты чата.
- `ChatOrchestrator`: выполняет жизненный цикл user-message как фоновой задачи.
Методы: `enqueue_message` — создает задачу и запускает обработку; `_process_task` — исполняет runtime и сохраняет результат; `_resolve_sessions` — валидирует и сопоставляет dialog/rag сессии.
- `TaskStore`: in-memory store состояний задач.
Методы: `create` — создает новую `TaskState`; `get` — возвращает задачу по `task_id`; `save` — обновляет состояние задачи.
- `DialogSessionStore`: хранилище dialog-сессий поверх БД.
Методы: `create` — создает новую dialog-сессию; `get` — читает dialog-сессию по id.
- `IdempotencyStore`: предотвращает дубль задач по идемпотентному ключу.
Методы: `get_task_id` — возвращает существующий `task_id` по ключу; `put` — сохраняет ключ и `task_id`.
- `EventBus`: асинхронная публикация/подписка событий.
Методы: `subscribe` — создает подписку на канал; `unsubscribe` — снимает подписку; `publish` — отправляет событие подписчикам; `as_sse` — сериализует событие в SSE формат.
- `AgentRunner` (контракт): интерфейс выполнения агентного запроса из chat-слоя.
Методы: `run` — принимает данные задачи и возвращает итог `answer`/`changeset`.
## 4. Сиквенс-диаграммы API
### POST /api/chat/dialogs
Назначение: создает новый диалог, связанный с существующей `rag_session`, чтобы пользователь мог отправлять сообщения в контексте конкретного индекса.
```mermaid
sequenceDiagram
participant Router as ChatModule.APIRouter
participant RagSessions as RagSessionStore
participant Dialogs as DialogSessionStore
Router->>RagSessions: get(rag_session_id)
RagSessions-->>Router: exists
Router->>Dialogs: create(rag_session_id)
Dialogs-->>Router: dialog_session
```
### POST /api/chat/messages
Назначение: ставит сообщение пользователя в асинхронную обработку и возвращает `task_id` для отслеживания результата.
```mermaid
sequenceDiagram
participant Router as ChatModule.APIRouter
participant Orchestrator as ChatOrchestrator
participant TaskStore as TaskStore
Router->>Orchestrator: enqueue_message(request, idempotency_key)
Orchestrator->>TaskStore: create()/save()
Orchestrator-->>Router: task_id,status
```
### GET /api/tasks/{task_id}
Назначение: отдает текущее состояние задачи и финальный результат (answer/changeset/error), когда обработка завершена.
```mermaid
sequenceDiagram
participant Router as ChatModule.APIRouter
participant TaskStore as TaskStore
Router->>TaskStore: get(task_id)
TaskStore-->>Router: task_state
```
### GET /api/events?task_id=...
Назначение: открывает SSE-поток с прогрессом выполнения задачи и промежуточными событиями.
```mermaid
sequenceDiagram
participant Router as ChatModule.APIRouter
participant Events as EventBus
Router->>Events: subscribe(task_id)
loop until disconnect
Events-->>Router: SSE event
end
Router->>Events: unsubscribe(task_id)
```
src/app/modules/chat/__init__.py
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src/app/modules/chat/dialog_store.py
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from __future__ import annotations
from dataclasses import dataclass
from typing import TYPE_CHECKING
from uuid import uuid4
if TYPE_CHECKING:
from app.modules.chat.repository import ChatRepository
@dataclass
class DialogSession:
dialog_session_id: str
rag_session_id: str
class DialogSessionStore:
def __init__(self, repository: ChatRepository) -> None:
self._repo = repository
def create(self, rag_session_id: str) -> DialogSession:
session = DialogSession(dialog_session_id=str(uuid4()), rag_session_id=rag_session_id)
self._repo.create_dialog(session.dialog_session_id, session.rag_session_id)
return session
def get(self, dialog_session_id: str) -> DialogSession | None:
row = self._repo.get_dialog(dialog_session_id)
if not row:
return None
return DialogSession(
dialog_session_id=str(row["dialog_session_id"]),
rag_session_id=str(row["rag_session_id"]),
)
src/app/modules/chat/direct_service.py
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from __future__ import annotations
import logging
from uuid import uuid4
from app.modules.agent.llm import AgentLlmService
from app.modules.chat.evidence_gate import CodeExplainEvidenceGate
from app.modules.chat.session_resolver import ChatSessionResolver
from app.modules.chat.task_store import TaskState, TaskStore
from app.modules.agent.runtime.steps.explain import CodeExplainRetrieverV2, PromptBudgeter
from app.schemas.chat import ChatMessageRequest, TaskQueuedResponse, TaskResultType, TaskStatus
LOGGER = logging.getLogger(__name__)
class CodeExplainChatService:
def __init__(
self,
retriever: CodeExplainRetrieverV2,
llm: AgentLlmService,
session_resolver: ChatSessionResolver,
task_store: TaskStore,
message_sink,
budgeter: PromptBudgeter | None = None,
evidence_gate: CodeExplainEvidenceGate | None = None,
) -> None:
self._retriever = retriever
self._llm = llm
self._session_resolver = session_resolver
self._task_store = task_store
self._message_sink = message_sink
self._budgeter = budgeter or PromptBudgeter()
self._evidence_gate = evidence_gate or CodeExplainEvidenceGate()
async def handle_message(self, request: ChatMessageRequest) -> TaskQueuedResponse:
dialog_session_id, rag_session_id = self._session_resolver.resolve(request)
task_id = str(uuid4())
task = TaskState(task_id=task_id, status=TaskStatus.RUNNING)
self._task_store.save(task)
self._message_sink(dialog_session_id, "user", request.message, task_id=task_id)
pack = self._retriever.build_pack(
rag_session_id,
request.message,
file_candidates=[item.model_dump(mode="json") for item in request.files],
)
decision = self._evidence_gate.evaluate(pack)
if decision.passed:
prompt_input = self._budgeter.build_prompt_input(request.message, pack)
answer = self._llm.generate(
"code_explain_answer_v2",
prompt_input,
log_context="chat.code_explain.direct",
).strip()
else:
answer = decision.answer
self._message_sink(dialog_session_id, "assistant", answer, task_id=task_id)
task.status = TaskStatus.DONE
task.result_type = TaskResultType.ANSWER
task.answer = answer
self._task_store.save(task)
LOGGER.warning(
"direct code explain response: task_id=%s rag_session_id=%s excerpts=%s missing=%s",
task_id,
rag_session_id,
len(pack.code_excerpts),
pack.missing,
)
return TaskQueuedResponse(
task_id=task_id,
status=TaskStatus.DONE.value,
)
src/app/modules/chat/evidence_gate.py
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from __future__ import annotations
from dataclasses import dataclass, field
from app.modules.agent.runtime.steps.explain.models import ExplainPack
@dataclass(slots=True)
class EvidenceGateDecision:
passed: bool
answer: str = ""
diagnostics: dict[str, list[str]] = field(default_factory=dict)
class CodeExplainEvidenceGate:
def __init__(self, min_excerpts: int = 2) -> None:
self._min_excerpts = min_excerpts
def evaluate(self, pack: ExplainPack) -> EvidenceGateDecision:
diagnostics = self._diagnostics(pack)
if len(pack.code_excerpts) >= self._min_excerpts:
return EvidenceGateDecision(passed=True, diagnostics=diagnostics)
return EvidenceGateDecision(
passed=False,
answer=self._build_answer(pack, diagnostics),
diagnostics=diagnostics,
)
def _diagnostics(self, pack: ExplainPack) -> dict[str, list[str]]:
return {
"entrypoints": [item.title for item in pack.selected_entrypoints[:3] if item.title],
"symbols": [item.title for item in pack.seed_symbols[:5] if item.title],
"paths": self._paths(pack),
"missing": list(pack.missing),
}
def _paths(self, pack: ExplainPack) -> list[str]:
values: list[str] = []
for item in pack.selected_entrypoints + pack.seed_symbols:
path = item.source or (item.location.path if item.location else "")
if path and path not in values:
values.append(path)
for excerpt in pack.code_excerpts:
if excerpt.path and excerpt.path not in values:
values.append(excerpt.path)
return values[:6]
def _build_answer(self, pack: ExplainPack, diagnostics: dict[str, list[str]]) -> str:
lines = [
"Недостаточно опоры в коде, чтобы дать объяснение без догадок.",
"",
f"Найдено фрагментов кода: {len(pack.code_excerpts)} из {self._min_excerpts} минимально необходимых.",
]
if diagnostics["paths"]:
lines.append(f"Пути: {', '.join(diagnostics['paths'])}")
if diagnostics["entrypoints"]:
lines.append(f"Entrypoints: {', '.join(diagnostics['entrypoints'])}")
if diagnostics["symbols"]:
lines.append(f"Символы: {', '.join(diagnostics['symbols'])}")
if diagnostics["missing"]:
lines.append(f"Диагностика: {', '.join(diagnostics['missing'])}")
return "\n".join(lines).strip()
src/app/modules/chat/module.py
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from __future__ import annotations
from typing import TYPE_CHECKING
from fastapi import APIRouter, Header
from fastapi.responses import StreamingResponse
from app.core.exceptions import AppError
from app.modules.chat.dialog_store import DialogSessionStore
from app.modules.chat.service import ChatOrchestrator
from app.modules.chat.task_store import TaskStore
from app.modules.shared.event_bus import EventBus
from app.modules.shared.idempotency_store import IdempotencyStore
from app.modules.shared.retry_executor import RetryExecutor
from app.schemas.chat import (
ChatMessageRequest,
DialogCreateRequest,
DialogCreateResponse,
TaskQueuedResponse,
TaskResultResponse,
)
from app.schemas.common import ModuleName
if TYPE_CHECKING:
from app.modules.chat.repository import ChatRepository
from app.modules.contracts import AgentRunner
from app.modules.rag.session_store import RagSessionStore
class ChatModule:
def __init__(
self,
agent_runner: AgentRunner,
event_bus: EventBus,
retry: RetryExecutor,
rag_sessions: RagSessionStore,
repository: ChatRepository,
task_store: TaskStore | None = None,
) -> None:
self._rag_sessions = rag_sessions
self.tasks = task_store or TaskStore()
self.dialogs = DialogSessionStore(repository)
self.idempotency = IdempotencyStore()
self.events = event_bus
self.chat = ChatOrchestrator(
task_store=self.tasks,
dialogs=self.dialogs,
idempotency=self.idempotency,
runtime=agent_runner,
events=self.events,
retry=retry,
rag_session_exists=lambda rag_session_id: rag_sessions.get(rag_session_id) is not None,
message_sink=repository.add_message,
)
def public_router(self) -> APIRouter:
router = APIRouter(tags=["chat"])
@router.post("/api/chat/dialogs", response_model=DialogCreateResponse)
async def create_dialog(request: DialogCreateRequest) -> DialogCreateResponse:
if not self._rag_sessions.get(request.rag_session_id):
raise AppError("rag_session_not_found", "RAG session not found", ModuleName.RAG)
dialog = self.dialogs.create(request.rag_session_id)
return DialogCreateResponse(
dialog_session_id=dialog.dialog_session_id,
rag_session_id=dialog.rag_session_id,
)
@router.post("/api/chat/messages", response_model=TaskQueuedResponse | TaskResultResponse)
async def send_message(
request: ChatMessageRequest,
idempotency_key: str | None = Header(default=None, alias="Idempotency-Key"),
) -> TaskQueuedResponse | TaskResultResponse:
task = await self.chat.enqueue_message(request, idempotency_key)
return TaskQueuedResponse(task_id=task.task_id, status=task.status.value)
@router.get("/api/tasks/{task_id}", response_model=TaskResultResponse)
async def get_task(task_id: str) -> TaskResultResponse:
task = self.tasks.get(task_id)
if not task:
raise AppError("not_found", f"Task not found: {task_id}", ModuleName.BACKEND)
return TaskResultResponse(
task_id=task.task_id,
status=task.status,
result_type=task.result_type,
answer=task.answer,
artifacts=task.artifacts,
changeset=task.changeset,
error=task.error,
)
@router.get("/api/events")
async def stream_events(task_id: str) -> StreamingResponse:
queue = await self.events.subscribe(task_id)
async def event_stream():
import asyncio
heartbeat = 10
try:
while True:
try:
event = await asyncio.wait_for(queue.get(), timeout=heartbeat)
yield EventBus.as_sse(event)
except asyncio.TimeoutError:
yield ": keepalive\\n\\n"
finally:
await self.events.unsubscribe(task_id, queue)
return StreamingResponse(event_stream(), media_type="text/event-stream")
return router
src/app/modules/chat/repository.py
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import json
from sqlalchemy import text
from app.modules.shared.db import get_engine
class ChatRepository:
def ensure_tables(self) -> None:
with get_engine().connect() as conn:
conn.execute(
text(
"""
CREATE TABLE IF NOT EXISTS dialog_sessions (
dialog_session_id VARCHAR(64) PRIMARY KEY,
rag_session_id VARCHAR(64) NOT NULL,
created_at TIMESTAMPTZ DEFAULT CURRENT_TIMESTAMP
)
"""
)
)
conn.execute(
text(
"""
CREATE TABLE IF NOT EXISTS chat_messages (
id BIGSERIAL PRIMARY KEY,
dialog_session_id VARCHAR(64) NOT NULL,
task_id VARCHAR(64),
role VARCHAR(16) NOT NULL,
content TEXT NOT NULL,
payload JSONB,
created_at TIMESTAMPTZ DEFAULT CURRENT_TIMESTAMP
)
"""
)
)
conn.execute(text("ALTER TABLE chat_messages ADD COLUMN IF NOT EXISTS task_id VARCHAR(64)"))
conn.execute(text("ALTER TABLE chat_messages ADD COLUMN IF NOT EXISTS payload JSONB"))
conn.commit()
def create_dialog(self, dialog_session_id: str, rag_session_id: str) -> None:
with get_engine().connect() as conn:
conn.execute(
text(
"""
INSERT INTO dialog_sessions (dialog_session_id, rag_session_id)
VALUES (:did, :sid)
"""
),
{"did": dialog_session_id, "sid": rag_session_id},
)
conn.commit()
def get_dialog(self, dialog_session_id: str) -> dict | None:
with get_engine().connect() as conn:
row = conn.execute(
text(
"""
SELECT dialog_session_id, rag_session_id
FROM dialog_sessions
WHERE dialog_session_id = :did
"""
),
{"did": dialog_session_id},
).mappings().fetchone()
return dict(row) if row else None
def add_message(
self,
dialog_session_id: str,
role: str,
content: str,
task_id: str | None = None,
payload: dict | None = None,
) -> None:
payload_json = json.dumps(payload, ensure_ascii=False) if payload is not None else None
with get_engine().connect() as conn:
conn.execute(
text(
"""
INSERT INTO chat_messages (dialog_session_id, task_id, role, content, payload)
VALUES (:did, :task_id, :role, :content, CAST(:payload AS JSONB))
"""
),
{
"did": dialog_session_id,
"task_id": task_id,
"role": role,
"content": content,
"payload": payload_json,
},
)
conn.commit()
src/app/modules/chat/service.py
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@@ -1,288 +0,0 @@
import asyncio
import logging
from app.core.exceptions import AppError
from app.modules.contracts import AgentRunner
from app.schemas.chat import ChatMessageRequest, TaskResultType, TaskStatus
from app.schemas.common import ErrorPayload, ModuleName
from app.modules.chat.dialog_store import DialogSessionStore
from app.modules.chat.session_resolver import ChatSessionResolver
from app.modules.chat.task_store import TaskState, TaskStore
from app.modules.shared.event_bus import EventBus
from app.modules.shared.idempotency_store import IdempotencyStore
from app.modules.shared.retry_executor import RetryExecutor
LOGGER = logging.getLogger(__name__)
def _truncate_for_log(text: str, max_chars: int = 1200) -> str:
value = (text or "").replace("\n", "\\n").strip()
if len(value) <= max_chars:
return value
return value[:max_chars].rstrip() + "...[truncated]"
class ChatOrchestrator:
def __init__(
self,
task_store: TaskStore,
dialogs: DialogSessionStore,
idempotency: IdempotencyStore,
runtime: AgentRunner,
events: EventBus,
retry: RetryExecutor,
rag_session_exists,
message_sink,
) -> None:
self._task_store = task_store
self._dialogs = dialogs
self._idempotency = idempotency
self._runtime = runtime
self._events = events
self._retry = retry
self._rag_session_exists = rag_session_exists
self._message_sink = message_sink
self._session_resolver = ChatSessionResolver(dialogs, rag_session_exists)
async def enqueue_message(
self,
request: ChatMessageRequest,
idempotency_key: str | None,
) -> TaskState:
if idempotency_key:
existing = self._idempotency.get_task_id(idempotency_key)
if existing:
task = self._task_store.get(existing)
if task:
LOGGER.info(
"enqueue_message reused task by idempotency key: task_id=%s mode=%s",
task.task_id,
request.mode.value,
)
return task
task = self._task_store.create()
if idempotency_key:
self._idempotency.put(idempotency_key, task.task_id)
asyncio.create_task(self._process_task(task.task_id, request))
LOGGER.info(
"enqueue_message created task: task_id=%s mode=%s",
task.task_id,
request.mode.value,
)
return task
async def _process_task(self, task_id: str, request: ChatMessageRequest) -> None:
task = self._task_store.get(task_id)
if not task:
return
task.status = TaskStatus.RUNNING
self._task_store.save(task)
await self._events.publish(task_id, "task_status", {"task_id": task_id, "status": task.status.value})
await self._publish_progress(task_id, "task.start", "Запрос принят, начинаю обработку.", progress=5)
heartbeat_stop = asyncio.Event()
heartbeat_task = asyncio.create_task(self._run_heartbeat(task_id, heartbeat_stop))
try:
await self._publish_progress(task_id, "task.sessions", "Проверяю сессии диалога и проекта.", progress=10)
dialog_session_id, rag_session_id = self._resolve_sessions(request)
LOGGER.warning(
"incoming chat request: task_id=%s dialog_session_id=%s rag_session_id=%s mode=%s attachments=%s files=%s message=%s",
task_id,
dialog_session_id,
rag_session_id,
request.mode.value,
len(request.attachments),
len(request.files),
_truncate_for_log(request.message),
)
await self._publish_progress(task_id, "task.sessions.done", "Сессии проверены, запускаю агента.", progress=15)
loop = asyncio.get_running_loop()
def progress_cb(stage: str, message: str, kind: str = "task_progress", meta: dict | None = None):
asyncio.run_coroutine_threadsafe(
self._events.publish(
task_id,
kind,
{
"task_id": task_id,
"stage": stage,
"message": message,
"meta": meta or {},
},
),
loop,
)
async def op():
self._message_sink(dialog_session_id, "user", request.message, task_id=task_id)
await self._publish_progress(task_id, "task.agent.run", "Агент анализирует запрос и готовит ответ.", progress=20)
return await self._runtime.run(
task_id=task_id,
dialog_session_id=dialog_session_id,
rag_session_id=rag_session_id,
mode=request.mode.value,
message=request.message,
attachments=[a.model_dump(mode="json") for a in request.attachments],
files=[f.model_dump(mode="json") for f in request.files],
progress_cb=progress_cb,
)
result = await self._retry.run(op)
await self._publish_progress(task_id, "task.finalize", "Сохраняю финальный результат.", progress=95)
task.status = TaskStatus.DONE
task.result_type = TaskResultType(result.result_type)
task.answer = result.answer
task.artifacts = list(getattr(result, "artifacts", []) or [])
task.changeset = result.changeset
if task.result_type != TaskResultType.CHANGESET and (task.answer or task.artifacts):
payload = {
"result_type": task.result_type.value,
"artifacts": [item.model_dump(mode="json") for item in task.artifacts],
}
self._message_sink(dialog_session_id, "assistant", task.answer or "", task_id=task_id, payload=payload)
LOGGER.warning(
"outgoing chat response: task_id=%s dialog_session_id=%s result_type=%s answer=%s",
task_id,
dialog_session_id,
task.result_type.value,
_truncate_for_log(task.answer or ""),
)
elif task.result_type == TaskResultType.CHANGESET:
self._message_sink(
dialog_session_id,
"assistant",
f"changeset:{len(task.changeset)}",
task_id=task_id,
payload={
"result_type": TaskResultType.CHANGESET.value,
"changeset": [item.model_dump(mode="json") for item in task.changeset],
},
)
LOGGER.warning(
"outgoing chat response: task_id=%s dialog_session_id=%s result_type=%s changeset_items=%s answer=%s",
task_id,
dialog_session_id,
task.result_type.value,
len(task.changeset),
_truncate_for_log(task.answer or ""),
)
self._task_store.save(task)
await self._events.publish(
task_id,
"task_result",
{
"task_id": task_id,
"status": task.status.value,
"result_type": task.result_type.value,
"answer": task.answer,
"artifacts": [item.model_dump(mode="json") for item in task.artifacts],
"changeset": [item.model_dump(mode="json") for item in task.changeset],
"meta": getattr(result, "meta", {}) or {},
},
)
await self._publish_progress(task_id, "task.done", "Обработка завершена.", progress=100)
LOGGER.info(
"_process_task completed: task_id=%s status=%s result_type=%s changeset_items=%s",
task_id,
task.status.value,
task.result_type.value if task.result_type else "",
len(task.changeset),
)
except (AppError, TimeoutError, ConnectionError, OSError) as exc:
task.status = TaskStatus.ERROR
if isinstance(exc, AppError):
payload = ErrorPayload(code=exc.code, desc=exc.desc, module=exc.module)
else:
payload = ErrorPayload(
code="retry_exhausted",
desc="Temporary failure after retries. Please retry request.",
module=ModuleName.BACKEND,
)
task.error = payload
self._task_store.save(task)
await self._publish_progress(task_id, "task.error", "Не удалось завершить обработку запроса.", kind="task_thinking")
await self._events.publish(task_id, "task_error", payload.model_dump(mode="json"))
LOGGER.warning(
"_process_task handled error: task_id=%s code=%s module=%s desc=%s",
task_id,
payload.code,
payload.module.value,
payload.desc,
)
except Exception:
task.status = TaskStatus.ERROR
payload = ErrorPayload(
code="agent_runtime_error",
desc="Agent execution failed unexpectedly. Please retry request.",
module=ModuleName.AGENT,
)
task.error = payload
self._task_store.save(task)
await self._publish_progress(
task_id,
"task.error",
"Во время выполнения возникла внутренняя ошибка.",
kind="task_thinking",
)
await self._events.publish(task_id, "task_error", payload.model_dump(mode="json"))
LOGGER.exception(
"_process_task unexpected error: task_id=%s code=%s",
task_id,
payload.code,
)
finally:
heartbeat_stop.set()
await heartbeat_task
async def _publish_progress(
self,
task_id: str,
stage: str,
message: str,
*,
progress: int | None = None,
kind: str = "task_progress",
meta: dict | None = None,
) -> None:
payload = {
"task_id": task_id,
"stage": stage,
"message": message,
"meta": meta or {},
}
if progress is not None:
payload["progress"] = max(0, min(100, int(progress)))
await self._events.publish(task_id, kind, payload)
LOGGER.debug(
"_publish_progress emitted: task_id=%s kind=%s stage=%s progress=%s",
task_id,
kind,
stage,
payload.get("progress"),
)
async def _run_heartbeat(self, task_id: str, stop_event: asyncio.Event) -> None:
messages = (
"Собираю данные по проекту.",
"Анализирую контекст и формирую структуру ответа.",
"Проверяю согласованность промежуточного результата.",
)
index = 0
while not stop_event.is_set():
try:
await asyncio.wait_for(stop_event.wait(), timeout=5.0)
except asyncio.TimeoutError:
await self._publish_progress(
task_id,
"task.heartbeat",
messages[index % len(messages)],
kind="task_thinking",
meta={"heartbeat": True},
)
index += 1
LOGGER.debug("_run_heartbeat stopped: task_id=%s ticks=%s", task_id, index)
def _resolve_sessions(self, request: ChatMessageRequest) -> tuple[str, str]:
return self._session_resolver.resolve(request)
src/app/modules/chat/session_resolver.py
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@@ -1,36 +0,0 @@
from __future__ import annotations
from typing import TYPE_CHECKING
from app.core.exceptions import AppError
from app.schemas.chat import ChatMessageRequest
from app.schemas.common import ModuleName
if TYPE_CHECKING:
from app.modules.chat.dialog_store import DialogSessionStore
class ChatSessionResolver:
def __init__(self, dialogs: DialogSessionStore, rag_session_exists) -> None:
self._dialogs = dialogs
self._rag_session_exists = rag_session_exists
def resolve(self, request: ChatMessageRequest) -> tuple[str, str]:
if request.dialog_session_id and request.rag_session_id:
dialog = self._dialogs.get(request.dialog_session_id)
if not dialog:
raise AppError("dialog_not_found", "Dialog session not found", ModuleName.BACKEND)
if dialog.rag_session_id != request.rag_session_id:
raise AppError("dialog_rag_mismatch", "Dialog session does not belong to rag session", ModuleName.BACKEND)
return request.dialog_session_id, request.rag_session_id
if request.session_id and request.project_id:
if not self._rag_session_exists(request.project_id):
raise AppError("rag_session_not_found", "RAG session not found", ModuleName.RAG)
return request.session_id, request.project_id
raise AppError(
"missing_sessions",
"dialog_session_id and rag_session_id are required",
ModuleName.BACKEND,
)
src/app/modules/chat/task_store.py
-38
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@@ -1,38 +0,0 @@
from dataclasses import dataclass, field
from threading import Lock
from uuid import uuid4
from app.schemas.changeset import ChangeItem
from app.schemas.chat import TaskArtifact, TaskResultType, TaskStatus
from app.schemas.common import ErrorPayload
@dataclass
class TaskState:
task_id: str
status: TaskStatus = TaskStatus.QUEUED
result_type: TaskResultType | None = None
answer: str | None = None
artifacts: list[TaskArtifact] = field(default_factory=list)
changeset: list[ChangeItem] = field(default_factory=list)
error: ErrorPayload | None = None
class TaskStore:
def __init__(self) -> None:
self._items: dict[str, TaskState] = {}
self._lock = Lock()
def create(self) -> TaskState:
task = TaskState(task_id=str(uuid4()))
with self._lock:
self._items[task.task_id] = task
return task
def get(self, task_id: str) -> TaskState | None:
with self._lock:
return self._items.get(task_id)
def save(self, task: TaskState) -> None:
with self._lock:
self._items[task.task_id] = task
src/app/modules/orchestration/__init__.py
-3
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@@ -1,3 +0,0 @@
from app.modules.orchestration.facade import OrchestrationFacade
__all__ = ["OrchestrationFacade"]
src/app/modules/orchestration/adapters/intent_router_adapter.py
-11
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@@ -1,11 +0,0 @@
from __future__ import annotations
from app.modules.agent.intent_router_v2 import IntentRouterV2
class IntentRouterAdapter:
def __init__(self, router: IntentRouterV2) -> None:
self._router = router
def route(self, user_query: str, conversation_state, repo_context):
return self._router.route(user_query, conversation_state, repo_context)
src/app/modules/orchestration/adapters/llm_chat_adapter.py
-19
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@@ -1,19 +0,0 @@
from __future__ import annotations
import asyncio
from app.modules.agent.llm.service import AgentLlmService
class LlmChatAdapter:
def __init__(self, llm: AgentLlmService, prompt_name: str = "agent_api_v1") -> None:
self._llm = llm
self._prompt_name = prompt_name
async def generate(self, message: str, request_id: str) -> str:
return await asyncio.to_thread(
self._llm.generate,
self._prompt_name,
message,
log_context=f"agent_api:{request_id}",
)
src/app/modules/orchestration/context/execution_context.py
-20
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@@ -1,20 +0,0 @@
from __future__ import annotations
from dataclasses import dataclass
from typing import Any
from app.modules.agent_api.domain.models.agent_request import AgentRequest
from app.modules.agent_api.domain.models.agent_session import AgentSession
from app.modules.agent_api.infrastructure.logging.request_trace_logger import RequestTraceLogger
from app.modules.orchestration.messaging.client_message_publisher import ClientMessagePublisher
@dataclass(slots=True)
class ExecutionContext:
request: AgentRequest
session: AgentSession
publisher: ClientMessagePublisher
trace_logger: RequestTraceLogger
task_context: Any = None
route_result: Any = None
workflow_result: Any = None
src/app/schemas/agent_api.py
+1 -1
View File
@@ -33,7 +33,7 @@ class ResetAgentSessionResponse(BaseModel):
class AgentRequestCreateRequest(BaseModel): class AgentRequestCreateRequest(BaseModel):
session_id: str = Field(min_length=1) session_id: str = Field(min_length=1)
message: str = Field(min_length=1) message: str = Field(min_length=1)
process_version: str = Field(default="v2", min_length=1) process_version: str = Field(default="v1", min_length=1)
class AgentRequestQueuedResponse(BaseModel): class AgentRequestQueuedResponse(BaseModel):
tests/unit_tests/chat/test_chat_api_simple_code_explain.py
-70
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@@ -1,70 +0,0 @@
import asyncio
from app.modules.chat.module import ChatModule
from app.modules.chat.task_store import TaskStore
from app.schemas.chat import ChatMessageRequest
from app.schemas.chat import TaskQueuedResponse
from app.modules.shared.event_bus import EventBus
from app.modules.shared.retry_executor import RetryExecutor
class _FakeRuntime:
async def run(self, **kwargs):
raise AssertionError("legacy runtime must not be called")
class _FakeDirectChat:
def __init__(self) -> None:
self.calls = 0
async def handle_message(self, request):
self.calls += 1
return TaskQueuedResponse(
task_id="task-1",
status="done",
)
class _FakeRagSessions:
def get(self, rag_session_id: str):
return {"rag_session_id": rag_session_id}
class _FakeRepository:
def create_dialog(self, dialog_session_id: str, rag_session_id: str) -> None:
return None
def get_dialog(self, dialog_session_id: str):
return None
def add_message(self, dialog_session_id: str, role: str, content: str, task_id: str | None = None, payload: dict | None = None) -> None:
return None
def test_chat_messages_endpoint_uses_direct_service(monkeypatch) -> None:
monkeypatch.setenv("SIMPLE_CODE_EXPLAIN_ONLY", "true")
direct_chat = _FakeDirectChat()
module = ChatModule(
agent_runner=_FakeRuntime(),
event_bus=EventBus(),
retry=RetryExecutor(),
rag_sessions=_FakeRagSessions(),
repository=_FakeRepository(),
direct_chat=direct_chat,
task_store=TaskStore(),
)
router = module.public_router()
endpoint = next(route.endpoint for route in router.routes if getattr(route, "path", "") == "/api/chat/messages")
response = asyncio.run(
endpoint(
ChatMessageRequest(
session_id="dialog-1",
project_id="rag-1",
message="Explain get_user",
),
None,
)
)
assert response.task_id == "task-1"
assert direct_chat.calls == 1
tests/unit_tests/chat/test_direct_service.py
-61
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@@ -1,61 +0,0 @@
import asyncio
from app.modules.chat.direct_service import CodeExplainChatService
from app.modules.chat.session_resolver import ChatSessionResolver
from app.modules.chat.task_store import TaskStore
from app.modules.agent.runtime.steps.explain.models import ExplainIntent, ExplainPack
from app.schemas.chat import ChatFileContext, ChatMessageRequest
class _FakeRetriever:
def build_pack(self, rag_session_id: str, user_query: str, *, file_candidates: list[dict] | None = None) -> ExplainPack:
return ExplainPack(
intent=ExplainIntent(raw_query=user_query, normalized_query=user_query),
missing=["code_excerpts"],
)
class _FakeLlm:
def __init__(self) -> None:
self.calls = 0
def generate(self, prompt_name: str, user_input: str, *, log_context: str | None = None) -> str:
self.calls += 1
return "should not be called"
class _FakeDialogs:
def get(self, dialog_session_id: str):
return None
def test_direct_service_skips_llm_when_evidence_is_insufficient() -> None:
messages: list[tuple[str, str, str, str | None]] = []
llm = _FakeLlm()
task_store = TaskStore()
service = CodeExplainChatService(
retriever=_FakeRetriever(),
llm=llm,
session_resolver=ChatSessionResolver(_FakeDialogs(), lambda rag_session_id: rag_session_id == "rag-1"),
task_store=task_store,
message_sink=lambda dialog_session_id, role, content, task_id=None: messages.append((dialog_session_id, role, content, task_id)),
)
result = asyncio.run(
service.handle_message(
ChatMessageRequest(
session_id="dialog-1",
project_id="rag-1",
message="Explain get_user",
files=[ChatFileContext(path="app/api/users.py", content="", content_hash="x")],
)
)
)
task = task_store.get(result.task_id)
assert task is not None
assert task.answer is not None
assert "Недостаточно опоры в коде" in task.answer
assert result.status == "done"
assert llm.calls == 0
assert [item[1] for item in messages] == ["user", "assistant"]