File size: 10,386 Bytes
6bff5d9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 | """ChatHandler — top-level Phase 2 chat orchestrator.
End-to-end flow per user message:
1. `IntentRouter.classify` → `chat` / `unstructured` / `structured`.
2. Route:
- `chat` → no context. Pass straight to ChatbotAgent.
- `structured` → CatalogReader → QueryService → QueryResult.
- `unstructured` → DocumentRetriever (placeholder, raises until TAB
ships) → list[DocumentChunk].
3. `ChatbotAgent.astream` → yield text tokens.
4. Wrap each step into an SSE-style event dict so the API endpoint can
stream them as Server-Sent Events.
Phase 1's chat endpoint (`src/api/v1/chat.py`) is intentionally NOT touched
in this PR. PR7 cleanup will rewire it to call `ChatHandler.handle(...)`.
All dependencies are injectable for tests. Default constructors lazy-build
production deps (no `Settings()` triggered at import time as long as you
inject mocks).
"""
from __future__ import annotations
import json
from collections.abc import AsyncIterator
from typing import TYPE_CHECKING, Any
from langchain_core.messages import BaseMessage
from src.middlewares.logging import get_logger
from src.retrieval.base import RetrievalResult
from .chatbot import ChatbotAgent, DocumentChunk
from .orchestration import OrchestratorAgent
if TYPE_CHECKING:
from ..catalog.reader import CatalogReader
from ..query.service import QueryService
from ..retrieval.router import RetrievalRouter
logger = get_logger("chat_handler")
class ChatHandler:
"""Top-level chat orchestrator.
Returns an `AsyncIterator[dict]` of SSE-style events with shape
`{"event": <name>, "data": <str>}`. Event types:
- `intent` — emitted once after classification (JSON-encoded decision)
- `sources` — JSON array of source refs (one per structured table, or
per (document_id, page_label) for unstructured)
- `chunk` — text fragment of the streaming answer (one per token)
- `done` — end of stream (data is empty string)
- `error` — failure; data is a user-facing message
"""
def __init__(
self,
intent_router: OrchestratorAgent | None = None,
answer_agent: ChatbotAgent | None = None,
catalog_reader: CatalogReader | None = None,
query_service: QueryService | None = None,
document_retriever: RetrievalRouter | None = None,
) -> None:
self._intent_router = intent_router
self._answer_agent = answer_agent
self._catalog_reader = catalog_reader
self._query_service = query_service
self._document_retriever = document_retriever
# ------------------------------------------------------------------
# Lazy default-dep builders
# ------------------------------------------------------------------
def _get_intent_router(self) -> OrchestratorAgent:
if self._intent_router is None:
self._intent_router = OrchestratorAgent()
return self._intent_router
def _get_answer_agent(self) -> ChatbotAgent:
if self._answer_agent is None:
self._answer_agent = ChatbotAgent()
return self._answer_agent
def _get_catalog_reader(self) -> CatalogReader:
if self._catalog_reader is None:
from ..catalog.reader import CatalogReader
from ..catalog.store import CatalogStore
self._catalog_reader = CatalogReader(CatalogStore())
return self._catalog_reader
def _get_query_service(self) -> QueryService:
if self._query_service is None:
from ..query.service import QueryService
self._query_service = QueryService()
return self._query_service
def _get_document_retriever(self) -> RetrievalRouter:
if self._document_retriever is None:
from ..retrieval.router import RetrievalRouter
self._document_retriever = RetrievalRouter()
return self._document_retriever
# ------------------------------------------------------------------
# Public entry
# ------------------------------------------------------------------
async def handle(
self,
message: str,
user_id: str,
history: list[BaseMessage] | None = None,
) -> AsyncIterator[dict[str, Any]]:
# ---- 1. Classify intent --------------------------------------
try:
decision = await self._get_intent_router().classify(message, history)
except Exception as e:
logger.error("intent classification failed", error=str(e))
yield {"event": "error", "data": f"Could not classify message: {e}"}
return
yield {"event": "intent", "data": decision.model_dump_json()}
rewritten = decision.rewritten_query or message
query_result = None
chunks: list[DocumentChunk] | None = None
raw_chunks: Any = None
# ---- 2. Route ------------------------------------------------
if decision.source_hint == "structured":
try:
catalog = await self._get_catalog_reader().read(user_id, "structured")
query_result = await self._get_query_service().run(
user_id, rewritten, catalog
)
except Exception as e:
logger.error(
"structured route failed",
user_id=user_id,
error=str(e),
)
yield {"event": "error", "data": f"Structured query failed: {e}"}
return
elif decision.source_hint == "unstructured":
try:
raw_chunks = await self._get_document_retriever().retrieve(
rewritten, user_id
)
chunks = _normalize_chunks(raw_chunks)
except NotImplementedError:
logger.warning("DocumentRetriever placeholder hit", user_id=user_id)
yield {
"event": "error",
"data": "Document retrieval is not yet available — pending implementation.",
}
return
except Exception as e:
logger.error(
"unstructured route failed", user_id=user_id, error=str(e)
)
yield {"event": "error", "data": f"Document retrieval failed: {e}"}
return
# else: chat path — no context
# ---- 2b. Emit sources ---------------------------------------
sources = _build_sources(
decision.source_hint, user_id, query_result, raw_chunks
)
yield {"event": "sources", "data": json.dumps(sources)}
# ---- 3. Stream answer ----------------------------------------
try:
async for token in self._get_answer_agent().astream(
message,
history=history,
query_result=query_result,
chunks=chunks,
):
yield {"event": "chunk", "data": token}
except Exception as e:
logger.error("answer streaming failed", user_id=user_id, error=str(e))
yield {"event": "error", "data": f"Answer generation failed: {e}"}
return
yield {"event": "done", "data": ""}
def _build_sources(
source_hint: str,
user_id: str,
query_result: Any,
raw_chunks: Any,
) -> list[dict[str, Any]]:
"""Build the sources payload for the SSE `sources` event.
- structured: one entry per executed table (table_name only).
- unstructured: deduped by (document_id, page_label), Phase 1 shape.
- chat or error: empty list.
"""
if source_hint == "structured":
if query_result is None or getattr(query_result, "error", None):
return []
table_name = getattr(query_result, "table_name", "") or ""
if not table_name:
return []
return [{
"document_id": f"{user_id}_{table_name}",
"filename": table_name,
"page_label": None,
}]
if source_hint == "unstructured" and raw_chunks:
seen: set[tuple[Any, Any]] = set()
sources: list[dict[str, Any]] = []
for item in raw_chunks:
if isinstance(item, RetrievalResult):
data = item.metadata.get("data", {})
elif isinstance(item, dict):
data = item
else:
continue
key = (data.get("document_id"), data.get("page_label"))
if key in seen or key == (None, None):
continue
seen.add(key)
sources.append({
"document_id": data.get("document_id"),
"filename": data.get("filename", "Unknown"),
"page_label": data.get("page_label", "Unknown"),
})
return sources
return []
def _normalize_chunks(raw: Any) -> list[DocumentChunk]:
"""Convert whatever the retriever returns into list[DocumentChunk].
The Phase 2 `DocumentRetriever.retrieve` interface is a stub today;
when TAB owner ships it, it should return `list[DocumentChunk]`
directly so this normalizer becomes a no-op. Until then we coerce
common shapes (dict-with-content, plain string) defensively.
"""
if not raw:
return []
if isinstance(raw, list) and all(isinstance(c, DocumentChunk) for c in raw):
return raw
chunks: list[DocumentChunk] = []
for item in raw:
if isinstance(item, DocumentChunk):
chunks.append(item)
elif isinstance(item, dict):
chunks.append(
DocumentChunk(
content=str(item.get("content", "")),
filename=item.get("filename"),
page_label=item.get("page_label"),
)
)
elif isinstance(item, RetrievalResult):
data = item.metadata.get("data", {})
page = data.get("page_label")
chunks.append(DocumentChunk(
content=item.content,
filename=data.get("filename"),
page_label=str(page) if page is not None else None,
))
elif isinstance(item, str):
chunks.append(DocumentChunk(content=item))
return chunks
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