Commit Graph
16 Commits
Author SHA1 Message Date
westfarn c5efe60e0b Add tier-gated RAG and Drive document sources (#42)
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Ship allows_rag entitlement (founders/backer/pro/business), enforce it on
document APIs and RAG chat, harden ingest/delete/active lifecycle, and add
Google/Microsoft Drive connect + sync for personal and company knowledge bases.

Closes #43 #44 #45 #46 #47 #48 #49 #50 #51 #52 #53
Parent epic: #42
Related: #11
2026-08-01 15:33:55 -05:00
westfarn 2e9e95e16c Stove-pipe RAG retrieval to prevent cross-tenant leakage (#40) (#41)
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## Summary

- Closes [#40](#40)
- Aligns chat/RAG with the abc_worker stove-pipe pattern ([b13cec8](b13cec88f9)): immutable `ChatCompanyScope` per turn, conversation ownership validation, fail-closed Chroma filters
- Prefer ASGI/JWT identity over client email; never bind identity from `conversation_id` alone
- Close `ConversationDetailView` IDOR (prompts only for `request.user`)

## Changes

- New `services/chat_tenant_scope.py` with frozen `ChatCompanyScope` + ownership checks
- WebSocket consumers (`consumers.py` / `consumers_graph.py`) validate scope before `get_messages` / RAG
- `search_documents` requires a workspace (no more `filter: None` over the shared collection)
- Ingest writes `company_id` metadata (retrieval still keys on `workspace_id` for back-compat)
- Legacy `get_retriever` always applies a workspace filter

## Test plan

- [x] `manage.py test chat_backend.tests.test_chat_tenant_scope chat_backend.tests.test_consumers chat_backend.tests.test_services_rag chat_backend.tests.test_views_conversations`
- [ ] Manual: user A cannot stream RAG context from user B `conversation_id`
- [ ] Manual: RAG still returns own-company docs after deploy (existing vectors with `workspace_id` only)
- [ ] Follow-up: FE can send JWT `token`/`access` on WS payloads for stronger identity bindingReviewed-on: #41
2026-08-01 12:35:00 -07:00
westfarn eedc842b08 Add account self-delete and subscription lifecycle sync (#34) (#39)
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## Summary
- Closes [#34](#34)
- Companion for [chat_web_app#75](ai_ml_operations/chat_web_app#75) (portal cancel/change local sync)
- Soft-delete `DELETE /api/user/` for the authenticated user only: `deleted=True`, `is_active=False`, hide conversations, blacklist outstanding refresh tokens; staff self-delete rejected
- Stripe `customer.subscription.updated` / `deleted` webhooks sync plan status, `cancel_at_period_end`, and `current_period_end`; checkout assigns plan from `metadata.plan_slug`
- **UserAuthEvent audit**: `account_deleted`, `subscription_started` (first active plan), `subscription_updated` (plan/status/cancel changes) — visible on user admin
- Document FE contract in README (endpoint, response, post-delete logout)

## Test plan
- [ ] `uv run python manage.py test chat_backend.tests.test_views_users.CustomUserSelfDeleteTestCase finance.tests`
- [ ] Authenticated `DELETE /api/user/` soft-deletes self, hides conversations, blocks re-login, writes `account_deleted` auth event
- [ ] Checkout / Backer assign writes `subscription_started`; portal cancel/change writes `subscription_updated`
- [ ] Anonymous / staff self-delete rejected; body cannot target another user
- [ ] After portal cancel, webhook sets `cancel_at_period_end` / `canceled` on `GET /finance/subscription/`Reviewed-on: #39
2026-08-01 12:24:17 -07:00
westfarn cc45ae5808 Persist Ollama token usage from streamed LLM responses (#16) (#38)
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## Summary
- Fixes token tracking for [#16](#16): streaming chat never persisted `PromptMetric.tokens_in` / `tokens_out` (admin + account usage showed `—`).
- Drop `StrOutputParser` on async LLM/RAG/data-analysis chains so Ollama `generation_info` (`prompt_eval_count` / `eval_count`) survives; collect usage while streaming via `TokenUsageCollector`.
- Stop calling `self.close()` in `disconnect` (fixes Grafana `Unexpected ASGI message 'websocket.close'`).

## Test plan
- [x] Unit tests: `test_utils`, consumers, LLM/RAG/data-analysis services, finance quotas
- [ ] Deploy / local: send a chat prompt, confirm admin Prompt Metrics shows Tokens In/Out
- [ ] Reload Account usage card — in/out no longer `—` for new turns
- [ ] Confirm WS disconnect no longer raises double-close in logsReviewed-on: #38
2026-07-31 10:46:57 -07:00
westfarn 9984d1c340 Name AI assistant Hesychia in system prompts (#22)
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## Summary
- Closes #20 — name the AI assistant **Hesychia** in system / generation prompts
- Add shared `assistant_identity.py` with `ASSISTANT_NAME` + concise calm/stillness tone
- Prepend identity to chat (`llm_service`), RAG, data analysis, and the views system message
- Document that identity lives in code (not env); add unit coverage

## Test plan
- [x] `uv run python manage.py test chat_backend.tests.test_assistant_identity chat_backend.tests.test_services_llm chat_backend.tests.test_services_data_analysis`
- [ ] Fresh chat: ask "who are you?" → responds as Hesychia
- [ ] Confirm classifiers/moderators/title generator unchanged (not assistant identity)

Related: companion frontend rebrand `chat_web_app#29`Reviewed-on: #22
2026-07-26 17:08:08 -07:00
westfarn 85637e3db6 Unpin langgraph stack; upgrade langchain-core instead (#14)
Unit Tests / test (push) Successful in 9s
Closes #10

## Summary
- Remove force-pins on `langgraph==1.0.4` / `langgraph-checkpoint==3.0.1` / `langgraph-prebuilt==1.0.5` / `langgraph-sdk==0.2.14`
- Upgrade langchain stack so current langgraph-checkpoint (4.x) works with `Reviver(allowed_objects=...)`
- Keep direct `langgraph>=1.2.5,<1.3.0` (matches langchain 1.3.x); checkpoint/prebuilt/sdk resolve transitively
- Adapt `BaseMessage.text()` → `.text` property for langchain-core 1.5.x

## Resolved versions (uv.lock)
| Package | Before | After |
|---|---|---|
| langchain-core | 1.1.1 | 1.5.1 |
| langchain | 1.1.2 | 1.3.14 |
| langgraph | 1.0.4 | 1.2.9 |
| langgraph-checkpoint | 3.0.1 | 4.1.1 |
| langgraph-prebuilt | 1.0.5 | 1.1.0 |
| langgraph-sdk | 0.2.14 | 0.4.2 |

## Test plan
- [x] `uv sync --frozen`
- [x] `uv run python manage.py test` — 248 OK (6 skipped)
- [x] Import `consumers_graph` CompiledStateGraph OK
- [x] Confirm `Reviver.__init__` accepts `allowed_objects`
- [ ] Manual smoke: WebSocket chat + graph path (`consumers_graph`)

## References
- Issue: #10
- Prior pin: #9Reviewed-on: #14
2026-07-26 05:11:39 -07:00
westfarn 0525f9559b Add offline unit test suite for chat_backend (#12)
Unit Tests / test (push) Successful in 9s
Closes #5

## Summary

- Replaces the three scattered test modules (`chat_backend/tests.py`, `services/tests.py`, `services/prompt_classifier/tests.py`) with a `chat_backend/tests/` package: **242 deterministic tests plus 6 opt-in live-Ollama checks**, up from 10 tests (3 of which were skipped and 4 of which were never even discovered).
- The suite runs fully offline — no Ollama, Chroma, SMTP or network access. LangChain runnables are replaced by a small `FakeChain`, Chroma/embeddings are mocked, email uses Django's locmem backend, and blobs go through `DatabaseStorage`.
- New `llm_be/test_runner.py` (wired via `TEST_RUNNER`) sets `SKIP_RAG_INIT=1` and an MD5 password hasher, so the suite cannot accidentally reach a model server and finishes in ~5s on SQLite (~17s on Postgres) instead of ~30s.

## Coverage

| Area | File |
|------|------|
| `TimeInfoBase.save`, slugs, `get_duration`, `file_exists`, cascades | `test_models.py` |
| `DatabaseStorage` save/open/exists/size/listdir/delete/times | `test_storage.py` |
| JWT claim, prompt/user/feedback/document serializers | `test_serializers.py` |
| auth + token, invite, feedback, company users, set-password, TOS | `test_views_users.py` |
| conversation list/order/create/detail/soft-delete | `test_views_conversations.py` |
| all four analytics endpoints, including empty-month behaviour | `test_views_analytics.py` |
| workspace + document upload/list/detail, 404 and 400 paths | `test_views_documents.py` |
| prompt classifier rules/parsing, moderation fail-safe, title cleanup | `test_services_classifiers.py` |
| CSV/XLSX/DOCX/PDF analysis, plot generation, error payloads | `test_services_data_analysis.py` |
| loader selection, filename sanitising, ingest, temp-file cleanup, search filters | `test_services_rag.py` |
| history formatting and streaming | `test_services_llm.py` |
| document re-index on create/delete, `SKIP_RAG_INIT` guard | `test_signals.py` |
| consumer DB helpers, LangGraph nodes (moderation, classification, generation, search flags), websocket routes | `test_consumers.py` |

Live checks (non-deterministic, need a model server):

```bash
cd llm_be
RUN_LIVE_OLLAMA_TESTS=1 uv run python manage.py test chat_backend.tests.test_live_ollama
```

## Bugs the tests surfaced (fixed here)

1. **`ConversationDetailView.post` silently dropped every prompt.** `import datetime` shadowed `from datetime import datetime`, so `datetime.now()` raised `AttributeError` inside a bare `except` and the endpoint returned 200 without saving. Now uses `timezone.now()`.
2. **Prompt attachments never reached the LLM.** `get_conversation_file_async` (both consumers) did `sync_to_async(prompt.file.read)` — with `DatabaseStorage` the attribute access itself opens the blob, i.e. a DB query in async context, raising `SynchronousOnlyOperation` that was swallowed and returned `(None, None)`. The read now happens inside the thread.
3. **`DatabaseStorage._save` crashed on a str-backed `ContentFile`** (`TypeError: sequence item 0: expected a bytes-like object`); chunks are encoded when needed.
4. **`services/prompt_classifier/__init__.,py`** (note the comma) meant the directory was only an implicit namespace package, which is why its test module was never collected. Renamed, and its duplicate live-Ollama tests folded into `test_live_ollama.py`.

Known-broken paths deliberately left untested and unchanged: `reset_password` / `ResetUserPassword` reference an unimported `requests` plus undefined locals, and `DocumentDetailView.get` references an undefined `workspaces` on its success path. Worth a follow-up ticket.

## Test plan

- [x] `cd llm_be && uv run python manage.py test` → 248 tests, OK (6 skipped, all opt-in live)
- [x] Same suite against Postgres 16 (`DATABASE_URL=postgres://…`) → OK, matching the containerized run in `deploy.yml`
- [x] `uv run black` clean on all added files
- [ ] Gitea Actions **Unit Tests** + **CI** green on this PRReviewed-on: #12
2026-07-26 05:00:17 -07:00
westfarn d1660792ad Dockerize chat_backend + Ollama LAN + DB file storage (#6) (#7)
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## Summary

Implements [chat_backend#6](#6) Part A:

- **uv** packaging (`pyproject.toml` + `uv.lock`), Docker/compose (dev + prod), entrypoint/validate-env, Gitea unit-test + auto-deploy workflows (mirror `scha`)
- Env-driven Django settings (`DJANGO_*`, `DATABASE_URL`, CSRF/CORS)
- **`OLLAMA_BASE_URL`** wired through all Ollama/LangChain clients (prod → `http://10.0.0.128:11434`)
- **DatabaseStorage** — prompt/document file blobs in Postgres (`StoredFile`), not container FS; RAG materializes temp paths for loaders
- ASGI via `gunicorn` + `UvicornWorker` (HTTP + WebSockets)

Companion server-infra PR registers `app_catalog` / `host_apps` (port **8003**).

## Test plan

- [ ] `uv sync && cd llm_be && SKIP_RAG_INIT=1 uv run python manage.py test`
- [ ] `docker compose build && docker compose up` against bundled Postgres
- [ ] Confirm Ollama calls use `OLLAMA_BASE_URL` (not hardcoded localhost)
- [ ] Upload a document / prompt file → row in `chat_backend_storedfile`, no disk under `media/`
- [ ] After server-infra merge + secret/Postgres/NPM: deploy via `deploy.sh --app chat_backend --env prod`Reviewed-on: #7
2026-07-25 05:23:33 -07:00
westfarn 77d7edd0dc Closes #4
Added site tracking
Can pick the model the use
Better handle llm model based on debug or not
2025-12-08 13:52:30 -06:00
westfarn eed1abedc8 updates 2025-12-07 06:31:06 -06:00
westfarn 91bdb2fd2d Merging from prod 2025-09-24 12:05:22 -05:00
westfarn 8a259158c8 Updated data analysis to generate images to perform data analysis 2025-09-24 11:49:08 -05:00
westfarn 14d8211715 Allow for data analysis 2025-09-08 12:29:20 -05:00
westfarn 951a58f2fa fixed chat service 2025-05-28 03:25:14 -05:00
westfarn a85f1222eb Syncing with updates from prod and formatted 2025-05-18 06:15:07 -05:00
westfarn f5d29166a6 RAG implementation, content moderation, prompt classification, new LLM chain, document storage 2025-05-14 03:27:38 -05:00