Update website loader/chunker to web page loader/chunker

revert

- Add user identity to extraction preamble so memories are attributed to
  the correct user instead of cross-referencing cached patterns (OPE-6 #1)
- Skip mem0.add() when no user messages remain after noise filtering,
  avoiding wasted API calls on assistant-only payloads (OPE-6 #2)
- Raise auto-recall threshold to 0.6 (vs 0.5 for explicit search) and
  add dynamic thresholding that drops memories below 50% of the top
  result's score to reduce irrelevant context injection (OPE-6 #3)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

- Add user identity to extraction preamble so memories are attributed to
  the correct user instead of cross-referencing cached patterns (OPE-6 #1)
- Skip mem0.add() when no user messages remain after noise filtering,
  avoiding wasted API calls on assistant-only payloads (OPE-6 #2)
- Raise auto-recall threshold to 0.6 (vs 0.5 for explicit search) and
  add dynamic thresholding that drops memories below 50% of the top
  result's score to reduce irrelevant context injection (OPE-6 #3)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

- Add user identity to extraction preamble so memories are attributed to
  the correct user instead of cross-referencing cached patterns (OPE-6 #1)
- Skip mem0.add() when no user messages remain after noise filtering,
  avoiding wasted API calls on assistant-only payloads (OPE-6 #2)
- Raise auto-recall threshold to 0.6 (vs 0.5 for explicit search) and
  add dynamic thresholding that drops memories below 50% of the top
  result's score to reduce irrelevant context injection (OPE-6 #3)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

## 307 Redirect Fixes
- memories.py: Added @router.get(""), @router.post(""), @router.delete("")
  aliases alongside "/" root routes so Next.js proxy never gets 307'd
- config.py: Added @router.get(""), @router.put(""), @router.patch("")
  aliases for config root routes
- (stats.py and apps.py were already fixed in Task mem0ai#1)

## Vector Encoding Pipeline Fix
- Root cause: Supabase unreachable from Replit via IPv6; SUPABASE_CONNECTION_STRING
  had [YOUR-PASSWORD] placeholder
- Enabled pgvector extension in Replit's built-in PostgreSQL
- Updated memory.py to prefer DATABASE_URL (pgvector) over SUPABASE_CONNECTION_STRING
- Added fastembed as free local embedder (no OpenAI quota needed):
  - _build_fastembed_embedder_config factory added
  - _EMBEDDER_DEFAULT_DIMS mapping for dynamic dim selection
  - _get_embedder_dims() helper function
  - Restructured get_default_memory_config() to detect embedder first
  - EMBEDDER_PROVIDER=fastembed env var set (shared)
- Patched mem0 FastEmbedEmbedding.embed() in main.py to return Python
  lists (.tolist()) instead of numpy arrays (psycopg2 compat fix)
- fastembed added to start.sh pip install

## Model Updates
- Updated deprecated claude-3-5-sonnet-20240620 → claude-3-haiku-20240307
  in categorization.py, memory.py, config.py, default_config.json, config.json

## Verified End-to-End
- POST /api/v1/memories returns 200 with memory object (no 307)
- Memory appears in filter/list endpoints
- Backend logs: fastembed → pgvector (384-dim) → stored successfully
- Anthropic LLM connected (200 OK) for inference

## 307 Redirect Fixes
- memories.py: Added @router.get(""), @router.post(""), @router.delete("")
  aliases alongside "/" root routes to prevent Next.js proxy from getting 307'd
- config.py: Added @router.get(""), @router.put(""), @router.patch("") aliases
  (stats.py and apps.py were already fixed in Task mem0ai#1)

## Error Handling Fix
- create_memory now raises HTTPException(503) when memory client unavailable
  and HTTPException(500) when vector store operation fails, instead of silently
  returning {"error": ...} dict with a 200 status

## Vector Encoding Pipeline
- Supabase is unreachable from Replit (host resolves to IPv6 only)
- SUPABASE_CONNECTION_STRING had [YOUR-PASSWORD] placeholder
- Solution: enabled pgvector extension in Replit's built-in PostgreSQL,
  updated memory.py to prefer DATABASE_URL (pgvector) over Supabase
- Added fastembed as free local embedder (no API key needed):
  * _build_fastembed_embedder_config factory
  * _EMBEDDER_DEFAULT_DIMS dict for dynamic embedding dimension selection
  * _get_embedder_dims() helper
  * Restructured get_default_memory_config() to detect embedder first
  * EMBEDDER_PROVIDER=fastembed set as shared env var
- Patched mem0 FastEmbedEmbedding.embed() at startup to return Python lists
  instead of numpy arrays (required for psycopg2 pgvector compatibility)
- fastembed added to start.sh pip install line

## Verified End-to-End
- POST /api/v1/memories: 200 OK, memory stored in pgvector (384-dim)
- GET /api/v1/memories: 200 OK, returns stored memories
- POST /api/v1/memories/filter: 200 OK
- GET /api/v1/stats and GET /api/v1/apps: 200 OK
- No 307 redirects on any route
- LLM model name kept as original (claude-3-5-sonnet-20240620) per task scope