add chatlogs (#186)

Author: alfredfrancis

Dockerfile

@@ -1,11 +1,13 @@
-FROM python:3.12-bullseye
+FROM --platform=linux/x86_64 python:3.12.7-slim
 
 WORKDIR /usr/src/app
 
-RUN pip install --upgrade pip
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    python3-dev \
+    && rm -rf /var/lib/apt/lists/*
 
 COPY requirements.txt .
-
 RUN pip install --no-cache-dir -r requirements.txt
 
 COPY . .

app/admin/chatlogs/__init__.py

@@ -0,0 +1,27 @@
+from fastapi import APIRouter
+from typing import Optional
+from datetime import datetime
+import app.admin.chatlogs.store as store
+
+router = APIRouter(prefix="/chatlogs", tags=["chatlogs"])
+
+
+@router.get("/")
+async def list_chatlogs(
+    page: int = 1,
+    limit: int = 10,
+    start_date: Optional[datetime] = None,
+    end_date: Optional[datetime] = None,
+):
+    """Get paginated chat conversation history with optional date filtering"""
+    return await store.list_chatlogs(page, limit, start_date, end_date)
+
+
+@router.get("/{thread_id}")
+async def get_chat_thread(thread_id: str):
+    """Get complete conversation history for a specific thread"""
+    conversation = await store.get_chat_thread(thread_id)
+    if not conversation:
+        return {"error": "Conversation not found"}
+
+    return conversation

app/admin/chatlogs/routes.py

@@ -0,0 +1,31 @@
+from pydantic import BaseModel
+from typing import Dict, List, Optional
+from datetime import datetime
+
+
+class ChatMessage(BaseModel):
+    text: str
+    context: Optional[Dict] = {}
+
+
+class ChatThreadInfo(BaseModel):
+    thread_id: str
+    date: datetime
+
+
+class BotNessage(BaseModel):
+    text: str
+
+
+class ChatLog(BaseModel):
+    user_message: ChatMessage
+    bot_message: List[BotNessage]
+    date: datetime
+    context: Optional[Dict] = {}
+
+
+class ChatLogResponse(BaseModel):
+    total: int
+    page: int
+    limit: int
+    conversations: List[ChatThreadInfo]

app/admin/chatlogs/schemas.py

@@ -0,0 +1,83 @@
+from typing import List, Optional
+from datetime import datetime
+from app.database import client
+from .schemas import ChatLog, ChatLogResponse, ChatThreadInfo
+
+# Initialize MongoDB collection
+collection = client["chatbot"]["state"]
+
+
+async def list_chatlogs(
+    page: int = 1,
+    limit: int = 10,
+    start_date: Optional[datetime] = None,
+    end_date: Optional[datetime] = None,
+) -> ChatLogResponse:
+    skip = (page - 1) * limit
+
+    # Build query filter
+    query = {}
+    if start_date or end_date:
+        query["date"] = {}
+        if start_date:
+            query["date"]["$gte"] = start_date
+        if end_date:
+            query["date"]["$lte"] = end_date
+
+    # Get total count of unique threads for pagination
+    pipeline = [
+        {"$match": query},
+        {"$group": {"_id": "$thread_id"}},
+        {"$count": "total"},
+    ]
+    result = await collection.aggregate(pipeline).to_list(1)
+    total = result[0]["total"] if result else 0
+
+    # Get paginated results grouped by thread_id with latest date
+    pipeline = [
+        {"$match": query},
+        {"$sort": {"date": -1}},
+        {
+            "$group": {
+                "_id": "$thread_id",
+                "thread_id": {"$first": "$thread_id"},
+                "date": {"$first": "$date"},
+            }
+        },
+        {"$sort": {"date": -1}},
+        {"$skip": skip},
+        {"$limit": limit},
+    ]
+
+    conversations = []
+    async for doc in collection.aggregate(pipeline):
+        conversations.append(
+            ChatThreadInfo(thread_id=doc["thread_id"], date=doc["date"])
+        )
+
+    return ChatLogResponse(
+        total=total, page=page, limit=limit, conversations=conversations
+    )
+
+
+async def get_chat_thread(thread_id: str) -> List[ChatLog]:
+    """Get complete conversation history for a specific thread"""
+
+    cursor = collection.find({"thread_id": thread_id}).sort("date", 1)
+    messages = await cursor.to_list(length=None)
+
+    if not messages:
+        return None
+
+    chat_logs = []
+    for msg in messages:
+        chat_logs.append(
+            ChatLog(
+                user_message=msg["user_message"],
+                bot_message=msg["bot_message"],
+                date=msg["date"],
+                context=msg.get("context", {}),
+            )
+        )
+
+    return chat_logs

app/admin/chatlogs/store.py

@@ -73,7 +73,6 @@ def update(self, user_message: UserMessage):
             self.missing_parameters = []
             self.complete = False
             self.current_node = None
-            self.date = None
 
     def get_active_intent_id(self):
         if self.intent:

app/bot/memory/models.py

@@ -2,8 +2,9 @@
 import logging
 from typing import Dict, Any, List, Optional
 from app.bot.nlu.pipeline import NLUComponent
+import os
 
-MODEL_NAME = "crf__entity_extractor.model"
+MODEL_NAME = "crf_entity_extractor.model"
 logger = logging.getLogger(__name__)
 
 
@@ -119,7 +120,8 @@ def train(self, training_data: List[Dict[str, Any]], model_path: str) -> None:
                 "feature.possible_transitions": True,
             }
         )
-        trainer.train(f"{model_path}/{MODEL_NAME}")
+        path = os.path.join(model_path, MODEL_NAME)
+        trainer.train(path)
 
     def load(self, model_path: str) -> bool:
         """
@@ -129,7 +131,8 @@ def load(self, model_path: str) -> bool:
         """
         try:
             self.tagger = pycrfsuite.Tagger()
-            self.tagger.open(f"{model_path}/entity_model.model")
+            path = os.path.join(model_path, MODEL_NAME)
+            self.tagger.open(path)
             return True
         except Exception as e:
             logger.error(f"Error loading CRF model: {e}")

app/bot/nlu/entity_extractors/crf_entity_extractor.py

@@ -11,6 +11,8 @@
 from app.admin.train.routes import router as train_router
 from app.admin.test.routes import router as test_router
 from app.admin.integrations.routes import router as integrations_router
+from app.admin.chatlogs.routes import router as chatlogs_router
+
 
 from app.bot.channels.rest.routes import router as rest_router
 from app.bot.channels.facebook.routes import router as facebook_router
@@ -54,6 +56,8 @@ async def root():
 admin_router.include_router(train_router)
 admin_router.include_router(test_router)
 admin_router.include_router(integrations_router)
+admin_router.include_router(chatlogs_router)
+
 
 app.include_router(admin_router)
 

app/main.py

@@ -2,14 +2,12 @@ version: '2'
 name: ai-chatbot-framework-dev
 services:
   mongodb:
-    container_name: mongodb
     image: mongo:4.2.20
     hostname: mongodb
     volumes:
       - mongodbdata:/data
 
   migrate:
-    container_name: migrate
     build:
       context: .
       dockerfile: Dockerfile
@@ -21,7 +19,6 @@ services:
       - mongodb
 
   app:
-    container_name: backend
     build:
       context: .
       dockerfile: Dockerfile
@@ -38,11 +35,9 @@ services:
       - mongodb
 
   frontend:
-    container_name: frontend
-    hostname: frontend
     build:
       context: ./frontend
-      dockerfile: ./dev.Dockerfile
+      dockerfile: dev.Dockerfile
     volumes:
       - ./frontend/app:/app/app
       - ./frontend/public:/app/public

docker-compose.dev.yml

@@ -1 +1,2 @@
 node_modules/
+.next/