feat: add appointments, campaigns, admin, storage, tests and various updates

- Add new routers: admin, appointments, campaigns
- Add storage service and logging config
- Add migrations directory and test suite with pytest config
- Add supabase_migration_features.sql
- Update models, dependencies, config, and existing routers
- Remove whatsapp_service (deleted)
- Update pyproject.toml and uv.lock dependencies

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

tests/test_rag.py

@@ -0,0 +1,118 @@
+"""Tests for RAG pipeline."""
+import pytest
+from unittest.mock import MagicMock, AsyncMock, patch
+
+
+class TestRAGEngine:
+    @pytest.fixture
+    def rag(self):
+        from app.services.rag import RAGEngine
+        engine = RAGEngine()
+        return engine
+
+    @pytest.fixture
+    def chatbot_config(self):
+        return {
+            "model": "accounts/fireworks/models/llama-v3p3-70b-instruct",
+            "max_tokens": 500,
+            "temperature": 0.7,
+            "company_name": "Test Corp",
+            "system_prompt": "You are helpful.",
+        }
+
+    async def test_returns_response_when_documents_found(self, rag, chatbot_config):
+        with patch.object(rag.embedding_svc, "embed_text", return_value=[0.1] * 1536), \
+             patch.object(rag.vector_svc, "search", return_value=[{
+                 "payload": {"text": "Test content", "file_name": "test.pdf", "page_number": 1},
+                 "score": 0.8,
+             }]), \
+             patch.object(rag.llm_svc, "generate", new_callable=AsyncMock, return_value={
+                 "content": "Test response",
+                 "tokens_used": 100,
+                 "model": "test-model",
+             }):
+
+            result = await rag.process_query(
+                query="What is the test?",
+                collection_name="test-collection",
+                chatbot_config=chatbot_config,
+                language="en",
+            )
+
+        assert result["response"] == "Test response"
+        assert len(result["sources"]) == 1
+        assert result["sources"][0].score == 0.8
+
+    async def test_returns_graceful_message_on_embedding_failure(self, rag, chatbot_config):
+        with patch.object(rag.embedding_svc, "embed_text", side_effect=Exception("Embedding failed")):
+            result = await rag.process_query(
+                query="Test query",
+                collection_name="test-collection",
+                chatbot_config=chatbot_config,
+            )
+
+        assert "trouble" in result["response"].lower()
+        assert result["sources"] == []
+
+    async def test_language_instruction_injected_for_french(self, rag, chatbot_config):
+        injected_prompt = None
+
+        async def capture_generate(messages, **kwargs):
+            nonlocal injected_prompt
+            injected_prompt = messages[0]["content"]
+            return {"content": "Bonjour", "tokens_used": 10, "model": "test"}
+
+        with patch.object(rag.embedding_svc, "embed_text", return_value=[0.1] * 1536), \
+             patch.object(rag.vector_svc, "search", return_value=[]), \
+             patch.object(rag.llm_svc, "generate", side_effect=capture_generate):
+
+            await rag.process_query(
+                query="Bonjour",
+                collection_name="test",
+                chatbot_config=chatbot_config,
+                language="fr",
+            )
+
+        assert injected_prompt is not None
+        assert "French" in injected_prompt
+
+    async def test_no_language_instruction_for_english(self, rag, chatbot_config):
+        injected_prompt = None
+
+        async def capture_generate(messages, **kwargs):
+            nonlocal injected_prompt
+            injected_prompt = messages[0]["content"]
+            return {"content": "Hello", "tokens_used": 10, "model": "test"}
+
+        with patch.object(rag.embedding_svc, "embed_text", return_value=[0.1] * 1536), \
+             patch.object(rag.vector_svc, "search", return_value=[]), \
+             patch.object(rag.llm_svc, "generate", side_effect=capture_generate):
+
+            await rag.process_query(
+                query="Hello",
+                collection_name="test",
+                chatbot_config=chatbot_config,
+                language="en",
+            )
+
+        assert injected_prompt is not None
+        # English should NOT inject a language instruction
+        assert "Respond in English" not in injected_prompt
+
+    async def test_empty_result_when_no_documents(self, rag, chatbot_config):
+        with patch.object(rag.embedding_svc, "embed_text", return_value=[0.1] * 1536), \
+             patch.object(rag.vector_svc, "search", return_value=[]), \
+             patch.object(rag.llm_svc, "generate", new_callable=AsyncMock, return_value={
+                 "content": "I don't have info on that.",
+                 "tokens_used": 20,
+                 "model": "test",
+             }):
+
+            result = await rag.process_query(
+                query="What is X?",
+                collection_name="empty-collection",
+                chatbot_config=chatbot_config,
+            )
+
+        assert result["sources"] == []
+        assert result["response"] == "I don't have info on that."