diff --git a/api/backend/ai/__init__.py b/api/backend/ai/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/api/backend/ai/ai_router.py b/api/backend/ai/ai_router.py
index d327c05..014f7da 100644
--- a/api/backend/ai/ai_router.py
+++ b/api/backend/ai/ai_router.py
@@ -1,66 +1,73 @@
 # STL
 import logging
-from collections.abc import Iterable, AsyncGenerator
+import asyncio
+from typing import AsyncGenerator, List, Dict, Any, cast
 
 # PDM
-from ollama import Message
-from fastapi import APIRouter
+from fastapi import APIRouter, HTTPException
 from fastapi.responses import JSONResponse, StreamingResponse
-from openai.types.chat import ChatCompletionMessageParam
+from langchain_core.messages import BaseMessage
+from langchain_core.runnables import RunnableConfig
+from langchain.callbacks.streaming_aiter import AsyncIteratorCallbackHandler
+from langchain_core.exceptions import LangChainException
 
 # LOCAL
+from api.backend.models import AI as AIRequestModel
 from api.backend.ai.clients import (
-    llama_model,
-    open_ai_key,
-    llama_client,
-    open_ai_model,
-    openai_client,
+    llm_instance,
+    provider_info,
+    AI_PROVIDER_BACKEND,
+    convert_to_langchain_messages,
 )
 from api.backend.ai.schemas import AI
 from api.backend.routers.handle_exceptions import handle_exceptions
 
 LOG = logging.getLogger("AI")
-
 ai_router = APIRouter()
 
-
-async def llama_chat(chat_messages: list[Message]) -> AsyncGenerator[str, None]:
-    if llama_client and llama_model:
+async def langchain_chat(messages: List[BaseMessage]) -> AsyncGenerator[str, None]:
+    if not llm_instance:
+        LOG.error("LLM instance not available")
+        yield "An error occurred: LLM not configured."
+        return
+    
+    callback_handler = AsyncIteratorCallbackHandler()
+    run_config = RunnableConfig(callbacks=[callback_handler])
+    
+    async def stream_llm_task():
         try:
-            async for part in await llama_client.chat(
-                model=llama_model, messages=chat_messages, stream=True
-            ):
-                yield part["message"]["content"]
+            async for _ in llm_instance.astream(messages, config=run_config):
+                pass  # Callback handler processes the chunks
+        except LangChainException as e:
+            LOG.error(f"LangChain error during streaming: {e}")
+            raise
         except Exception as e:
-            LOG.error(f"Error during chat: {e}")
-            yield "An error occurred while processing your request."
-
-
-async def openai_chat(
-    chat_messages: Iterable[ChatCompletionMessageParam],
-) -> AsyncGenerator[str, None]:
-    if openai_client and not open_ai_model:
-        LOG.error("OpenAI model is not set")
-        yield "An error occurred while processing your request."
-
-    if not openai_client:
-        LOG.error("OpenAI client is not set")
-        yield "An error occurred while processing your request."
-
-    if openai_client and open_ai_model:
-        try:
-            response = openai_client.chat.completions.create(
-                model=open_ai_model, messages=chat_messages, stream=True
-            )
-            for part in response:
-                yield part.choices[0].delta.content or ""
-        except Exception as e:
-            LOG.error(f"Error during OpenAI chat: {e}")
-            yield "An error occurred while processing your request."
-
-
-chat_function = llama_chat if llama_client else openai_chat
-
+            LOG.error(f"Unexpected error during LLM streaming: {e}", exc_info=True)
+            raise
+        finally:
+            if not callback_handler.done.is_set():
+                callback_handler.done.set()
+    
+    stream_task = asyncio.create_task(stream_llm_task())
+    
+    try:
+        async for token in callback_handler.aiter():
+            yield token
+    except Exception as e:
+        LOG.error(f"Error in streaming response: {e}", exc_info=True)
+        yield f"Streaming error: {str(e)}"
+    finally:
+        if not stream_task.done():
+            stream_task.cancel()
+            try:
+                await stream_task
+            except asyncio.CancelledError:
+                LOG.debug("Stream task cancelled successfully")
+            except Exception as e:
+                LOG.error(f"Error during stream task cleanup: {e}")
+
+
+chat_function = langchain_chat if llm_instance else None
 
 @ai_router.post("/ai")
 @handle_exceptions(logger=LOG)
@@ -73,4 +80,8 @@ async def ai(c: AI):
 @ai_router.get("/ai/check")
 @handle_exceptions(logger=LOG)
 async def check():
-    return JSONResponse(content={"ai_enabled": bool(open_ai_key or llama_model)})
+    return JSONResponse(content={
+        "ai_system_enabled": bool(llm_instance and provider_info.get("configured", False)),
+        "configured_backend_provider": AI_PROVIDER_BACKEND,
+        "active_provider_details": provider_info
+    })
\ No newline at end of file
diff --git a/api/backend/ai/clients.py b/api/backend/ai/clients.py
index 04c7e7d..4eb71a4 100644
--- a/api/backend/ai/clients.py
+++ b/api/backend/ai/clients.py
@@ -1,39 +1,194 @@
 # STL
 import os
+import logging
+from typing import Optional, Dict, Any, List
 
 # PDM
-from ollama import AsyncClient
-from openai import OpenAI
+from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage, AIMessage
+from langchain_core.language_models.chat_models import BaseChatModel
+from langchain_openai import ChatOpenAI
+from langchain_community.chat_models import ChatOllama
 
-# Load environment variables
-open_ai_key = os.getenv("OPENAI_KEY")
-open_ai_model = os.getenv("OPENAI_MODEL")
-llama_url = os.getenv("OLLAMA_URL")
-llama_model = os.getenv("OLLAMA_MODEL")
+LOG = logging.getLogger(__name__)
 
-# Initialize clients
-openai_client = OpenAI(api_key=open_ai_key) if open_ai_key else None
-llama_client = AsyncClient(host=llama_url) if llama_url else None
+# Environment variables
+AI_PROVIDER_BACKEND = os.getenv("AI_PROVIDER_BACKEND")
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+OPENAI_MODEL_NAME = os.getenv("OPENAI_MODEL_NAME")
+OLLAMA_BASE_URL = os.getenv("OLLAMA_BASE_URL")
+OLLAMA_MODEL_NAME = os.getenv("OLLAMA_MODEL_NAME")
+OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
+OPENROUTER_MODEL_NAME = os.getenv("OPENROUTER_MODEL_NAME")
 
+# Global state
+llm_instance: Optional[BaseChatModel] = None
+provider_info: Dict[str, Any] = {
+    "name": "None", 
+    "model": None, 
+    "configured": False, 
+    "error": None
+}
 
-async def ask_open_ai(prompt: str) -> str:
-    if not openai_client:
-        raise ValueError("OpenAI client not initialized")
 
-    response = openai_client.chat.completions.create(
-        model=open_ai_model or "gpt-4.1-mini",
-        messages=[{"role": "user", "content": prompt}],
-    )
+class ChatOpenRouter(ChatOpenAI):
+    """Custom OpenRouter client extending ChatOpenAI."""
+    
+    def __init__(self, openai_api_key: Optional[str] = None, **kwargs):
+        api_key = openai_api_key or os.environ.get("OPENROUTER_API_KEY")
+        super().__init__(
+            base_url="https://openrouter.ai/api/v1",
+            openai_api_key=api_key,
+            **kwargs
+        )
 
-    return response.choices[0].message.content or ""
 
+def create_openai_provider() -> tuple[Optional[BaseChatModel], Dict[str, Any]]:
+    """Create OpenAI provider instance."""
+    if not OPENAI_API_KEY or not OPENAI_MODEL_NAME:
+        error_msg = "OpenAI API key or model name not provided."
+        return None, {"name": "OpenAI", "configured": False, "error": error_msg}
+    
+    try:
+        llm = ChatOpenAI(
+            model=OPENAI_MODEL_NAME,
+            api_key=OPENAI_API_KEY,
+            streaming=True,
+            temperature=0.7,
+        )
+        info = {"name": "OpenAI", "model": OPENAI_MODEL_NAME, "configured": True}
+        LOG.info(f"Initialized OpenAI provider. Model: {OPENAI_MODEL_NAME}")
+        return llm, info
+    except Exception as e:
+        error_msg = f"Failed to initialize OpenAI provider: {e}"
+        LOG.error(error_msg)
+        return None, {"name": "OpenAI", "configured": False, "error": error_msg}
 
-async def ask_ollama(prompt: str) -> str:
-    if not llama_client:
-        raise ValueError("Ollama client not initialized")
 
-    response = await llama_client.chat(
-        model=llama_model or "", messages=[{"role": "user", "content": prompt}]
-    )
+def create_ollama_provider() -> tuple[Optional[BaseChatModel], Dict[str, Any]]:
+    if not OLLAMA_BASE_URL or not OLLAMA_MODEL_NAME:
+        error_msg = "Ollama base URL or model name not provided."
+        return None, {"name": "Ollama", "configured": False, "error": error_msg}
+    
+    try:
+        llm = ChatOllama(
+            base_url=OLLAMA_BASE_URL,
+            model=OLLAMA_MODEL_NAME,
+            temperature=0.7,
+        )
+        info = {"name": "Ollama", "model": OLLAMA_MODEL_NAME, "configured": True}
+        LOG.info(f"Initialized Ollama provider. Model: {OLLAMA_MODEL_NAME}, URL: {OLLAMA_BASE_URL}")
+        return llm, info
+    except Exception as e:
+        error_msg = f"Failed to initialize Ollama provider: {e}"
+        LOG.error(error_msg)
+        return None, {"name": "Ollama", "configured": False, "error": error_msg}
 
-    return response.message.content or ""
+
+def create_openrouter_provider() -> tuple[Optional[BaseChatModel], Dict[str, Any]]:
+    if not OPENROUTER_API_KEY or not OPENROUTER_MODEL_NAME:
+        error_msg = "OpenRouter API key or model name not provided."
+        return None, {"name": "OpenRouter", "configured": False, "error": error_msg}
+    
+    try:
+        llm = ChatOpenRouter(
+            model=OPENROUTER_MODEL_NAME,
+            openai_api_key=OPENROUTER_API_KEY,
+            streaming=True,
+            temperature=0.7,
+        )
+        info = {"name": "OpenRouter", "model": OPENROUTER_MODEL_NAME, "configured": True}
+        LOG.info(f"Initialized OpenRouter provider. Model: {OPENROUTER_MODEL_NAME}")
+        return llm, info
+    except Exception as e:
+        error_msg = f"Failed to initialize OpenRouter provider: {e}"
+        LOG.error(error_msg)
+        return None, {"name": "OpenRouter", "configured": False, "error": error_msg}
+
+
+def initialize_ai_provider() -> None:
+    global llm_instance, provider_info
+    
+    if not AI_PROVIDER_BACKEND:
+        provider_info.update({"configured": False, "error": "No AI provider specified"})
+        return
+    
+    LOG.info(f"Initializing AI provider: {AI_PROVIDER_BACKEND}")
+    
+    provider_factories = {
+        "openai": create_openai_provider,
+        "ollama": create_ollama_provider, 
+        "openrouter": create_openrouter_provider,
+    }
+    
+    factory = provider_factories.get(AI_PROVIDER_BACKEND)
+    if not factory:
+        error_msg = f"Unsupported AI provider: {AI_PROVIDER_BACKEND}"
+        LOG.error(error_msg)
+        provider_info.update({"configured": False, "error": error_msg})
+        return
+    
+    try:
+        llm_instance, provider_info = factory()
+    except ImportError as e:
+        error_msg = f"Missing dependencies for {AI_PROVIDER_BACKEND}: {e}"
+        LOG.error(error_msg)
+        provider_info.update({"configured": False, "error": error_msg})
+    except Exception as e:
+        error_msg = f"Unexpected error initializing {AI_PROVIDER_BACKEND}: {e}"
+        LOG.error(error_msg, exc_info=True)
+        provider_info.update({"configured": False, "error": error_msg})
+
+
+def convert_to_langchain_messages(messages: List[Dict[str, Any]]) -> List[BaseMessage]:
+    lc_messages: List[BaseMessage] = []
+    
+    for msg_dict in messages:
+        role = str(msg_dict.get("role", "user")).lower()
+        content = str(msg_dict.get("content", ""))
+        
+        if role == "user":
+            lc_messages.append(HumanMessage(content=content))
+        elif role in ("assistant", "ai"):
+            lc_messages.append(AIMessage(content=content))
+        elif role == "system":
+            lc_messages.append(SystemMessage(content=content))
+        else:
+            LOG.warning(f"Unknown message role '{role}', treating as user message")
+            lc_messages.append(HumanMessage(content=content))
+    
+    return lc_messages
+
+
+async def ask_llm(prompt: str) -> str:
+    """Simple non-streaming LLM query (similar to your old ask_open_ai/ask_ollama)."""
+    if not llm_instance:
+        raise ValueError("LLM client not initialized")
+    
+    try:
+        messages = [HumanMessage(content=prompt)]
+        response = await llm_instance.ainvoke(messages)
+        
+        content = response.content
+        if not content:
+            return ""
+        
+        if not isinstance(content, list):
+            return str(content)
+        
+        text_parts: List[str] = []
+        for item in content:
+            if not isinstance(item, dict):
+                text_parts.append(str(item))
+            else:
+                text_value = item.get("text")
+                if text_value is not None:
+                    text_parts.append(str(text_value))
+                    
+        return " ".join(text_parts) if text_parts else ""
+            
+    except Exception as e:
+        LOG.error(f"Error in LLM query: {e}")
+        raise
+
+
+initialize_ai_provider()
diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml
index c44c1f2..4598c32 100644
--- a/docker-compose.dev.yml
+++ b/docker-compose.dev.yml
@@ -18,6 +18,13 @@ services:
       dockerfile: docker/api/Dockerfile
     environment:
       - LOG_LEVEL=INFO
+      - AI_PROVIDER_BACKEND=  # openai | ollama | openrouter | (leave empty to disable ai)
+      - OPENAI_API_KEY=''
+      - OPENAI_MODEL_NAME='gpt4o'
+      - OLLAMA_BASE_URL=http://localhost:11434
+      - OLLAMA_MODEL_NAME=llama2
+      - OPENROUTER_API_KEY=''
+      - OPENROUTER_MODEL_NAME='openai/gpt-4'
     volumes:
       - "$PWD/api:/project/app/api"
     ports:
diff --git a/docker-compose.yml b/docker-compose.yml
index 5c7d6e2..affcd5c 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -15,7 +15,13 @@ services:
     image: jpyles0524/scraperr_api:latest
     environment:
       - LOG_LEVEL=INFO
-      - OPENAI_KEY=${OPENAI_KEY}
+      - AI_PROVIDER_BACKEND=  # openai | ollama | openrouter | (leave empty to disable ai)
+      - OPENAI_API_KEY=''
+      - OPENAI_MODEL_NAME='gpt4o'
+      - OLLAMA_BASE_URL=http://localhost:11434
+      - OLLAMA_MODEL_NAME=llama2
+      - OPENROUTER_API_KEY=''
+      - OPENROUTER_MODEL_NAME='openai/gpt-4'
     container_name: scraperr_api
     ports:
       - 8000:8000
diff --git a/pdm.lock b/pdm.lock
index e07823c..e4f6115 100644
--- a/pdm.lock
+++ b/pdm.lock
@@ -223,14 +223,17 @@ files = [
 
 [[package]]
 name = "async-timeout"
-version = "5.0.1"
-requires_python = ">=3.8"
+version = "4.0.3"
+requires_python = ">=3.7"
 summary = "Timeout context manager for asyncio programs"
 groups = ["default"]
 marker = "python_version < \"3.11\""
+dependencies = [
+    "typing-extensions>=3.6.5; python_version < \"3.8\"",
+]
 files = [
-    {file = "async_timeout-5.0.1-py3-none-any.whl", hash = "sha256:39e3809566ff85354557ec2398b55e096c8364bacac9405a7a1fa429e77fe76c"},
-    {file = "async_timeout-5.0.1.tar.gz", hash = "sha256:d9321a7a3d5a6a5e187e824d2fa0793ce379a202935782d555d6e9d2735677d3"},
+    {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
+    {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
 ]
 
 [[package]]
@@ -783,6 +786,21 @@ files = [
     {file = "cython-3.1.0.tar.gz", hash = "sha256:1097dd60d43ad0fff614a57524bfd531b35c13a907d13bee2cc2ec152e6bf4a1"},
 ]
 
+[[package]]
+name = "dataclasses-json"
+version = "0.6.7"
+requires_python = "<4.0,>=3.7"
+summary = "Easily serialize dataclasses to and from JSON."
+groups = ["default"]
+dependencies = [
+    "marshmallow<4.0.0,>=3.18.0",
+    "typing-inspect<1,>=0.4.0",
+]
+files = [
+    {file = "dataclasses_json-0.6.7-py3-none-any.whl", hash = "sha256:0dbf33f26c8d5305befd61b39d2b3414e8a407bedc2834dea9b8d642666fb40a"},
+    {file = "dataclasses_json-0.6.7.tar.gz", hash = "sha256:b6b3e528266ea45b9535223bc53ca645f5208833c29229e847b3f26a1cc55fc0"},
+]
+
 [[package]]
 name = "decorator"
 version = "5.2.1"
@@ -1217,6 +1235,17 @@ files = [
     {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"},
 ]
 
+[[package]]
+name = "httpx-sse"
+version = "0.4.0"
+requires_python = ">=3.8"
+summary = "Consume Server-Sent Event (SSE) messages with HTTPX."
+groups = ["default"]
+files = [
+    {file = "httpx-sse-0.4.0.tar.gz", hash = "sha256:1e81a3a3070ce322add1d3529ed42eb5f70817f45ed6ec915ab753f961139721"},
+    {file = "httpx_sse-0.4.0-py3-none-any.whl", hash = "sha256:f329af6eae57eaa2bdfd962b42524764af68075ea87370a2de920af5341e318f"},
+]
+
 [[package]]
 name = "hyperframe"
 version = "6.1.0"
@@ -1372,6 +1401,31 @@ files = [
     {file = "jmespath-1.0.1.tar.gz", hash = "sha256:90261b206d6defd58fdd5e85f478bf633a2901798906be2ad389150c5c60edbe"},
 ]
 
+[[package]]
+name = "jsonpatch"
+version = "1.33"
+requires_python = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
+summary = "Apply JSON-Patches (RFC 6902) "
+groups = ["default"]
+dependencies = [
+    "jsonpointer>=1.9",
+]
+files = [
+    {file = "jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade"},
+    {file = "jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c"},
+]
+
+[[package]]
+name = "jsonpointer"
+version = "3.0.0"
+requires_python = ">=3.7"
+summary = "Identify specific nodes in a JSON document (RFC 6901) "
+groups = ["default"]
+files = [
+    {file = "jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942"},
+    {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"},
+]
+
 [[package]]
 name = "jwcrypto"
 version = "1.5.6"
@@ -1401,6 +1455,124 @@ files = [
     {file = "kaitaistruct-0.10.tar.gz", hash = "sha256:a044dee29173d6afbacf27bcac39daf89b654dd418cfa009ab82d9178a9ae52a"},
 ]
 
+[[package]]
+name = "langchain"
+version = "0.3.25"
+requires_python = ">=3.9"
+summary = "Building applications with LLMs through composability"
+groups = ["default"]
+dependencies = [
+    "PyYAML>=5.3",
+    "SQLAlchemy<3,>=1.4",
+    "async-timeout<5.0.0,>=4.0.0; python_version < \"3.11\"",
+    "langchain-core<1.0.0,>=0.3.58",
+    "langchain-text-splitters<1.0.0,>=0.3.8",
+    "langsmith<0.4,>=0.1.17",
+    "pydantic<3.0.0,>=2.7.4",
+    "requests<3,>=2",
+]
+files = [
+    {file = "langchain-0.3.25-py3-none-any.whl", hash = "sha256:931f7d2d1eaf182f9f41c5e3272859cfe7f94fc1f7cef6b3e5a46024b4884c21"},
+    {file = "langchain-0.3.25.tar.gz", hash = "sha256:a1d72aa39546a23db08492d7228464af35c9ee83379945535ceef877340d2a3a"},
+]
+
+[[package]]
+name = "langchain-community"
+version = "0.3.24"
+requires_python = ">=3.9"
+summary = "Community contributed LangChain integrations."
+groups = ["default"]
+dependencies = [
+    "PyYAML>=5.3",
+    "SQLAlchemy<3,>=1.4",
+    "aiohttp<4.0.0,>=3.8.3",
+    "dataclasses-json<0.7,>=0.5.7",
+    "httpx-sse<1.0.0,>=0.4.0",
+    "langchain-core<1.0.0,>=0.3.59",
+    "langchain<1.0.0,>=0.3.25",
+    "langsmith<0.4,>=0.1.125",
+    "numpy>=1.26.2; python_version < \"3.13\"",
+    "numpy>=2.1.0; python_version >= \"3.13\"",
+    "pydantic-settings<3.0.0,>=2.4.0",
+    "requests<3,>=2",
+    "tenacity!=8.4.0,<10,>=8.1.0",
+]
+files = [
+    {file = "langchain_community-0.3.24-py3-none-any.whl", hash = "sha256:b6cdb376bf1c2f4d2503aca20f8f35f2d5b3d879c52848277f20ce1950e7afaf"},
+    {file = "langchain_community-0.3.24.tar.gz", hash = "sha256:62d9e8cf9aadf35182ec3925f9ec1c8e5e84fb4f199f67a01aee496d289dc264"},
+]
+
+[[package]]
+name = "langchain-core"
+version = "0.3.60"
+requires_python = ">=3.9"
+summary = "Building applications with LLMs through composability"
+groups = ["default"]
+dependencies = [
+    "PyYAML>=5.3",
+    "jsonpatch<2.0,>=1.33",
+    "langsmith<0.4,>=0.1.126",
+    "packaging<25,>=23.2",
+    "pydantic>=2.7.4",
+    "tenacity!=8.4.0,<10.0.0,>=8.1.0",
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+
 [[package]]
 name = "requests"
 version = "2.32.3"
@@ -3083,6 +3367,54 @@ files = [
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 ]
 
+[[package]]
+name = "sqlalchemy"
+version = "2.0.41"
+requires_python = ">=3.7"
+summary = "Database Abstraction Library"
+groups = ["default"]
+dependencies = [
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+    "importlib-metadata; python_version < \"3.8\"",
+    "typing-extensions>=4.6.0",
+]
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+    {file = "sqlalchemy-2.0.41-cp313-cp313-win_amd64.whl", hash = "sha256:82ca366a844eb551daff9d2e6e7a9e5e76d2612c8564f58db6c19a726869c1df"},
+    {file = "sqlalchemy-2.0.41-py3-none-any.whl", hash = "sha256:57df5dc6fdb5ed1a88a1ed2195fd31927e705cad62dedd86b46972752a80f576"},
+    {file = "sqlalchemy-2.0.41.tar.gz", hash = "sha256:edba70118c4be3c2b1f90754d308d0b79c6fe2c0fdc52d8ddf603916f83f4db9"},
+]
+
 [[package]]
 name = "stack-data"
 version = "0.6.3"
@@ -3113,6 +3445,55 @@ files = [
     {file = "starlette-0.46.2.tar.gz", hash = "sha256:7f7361f34eed179294600af672f565727419830b54b7b084efe44bb82d2fccd5"},
 ]
 
+[[package]]
+name = "tenacity"
+version = "9.1.2"
+requires_python = ">=3.9"
+summary = "Retry code until it succeeds"
+groups = ["default"]
+files = [
+    {file = "tenacity-9.1.2-py3-none-any.whl", hash = "sha256:f77bf36710d8b73a50b2dd155c97b870017ad21afe6ab300326b0371b3b05138"},
+    {file = "tenacity-9.1.2.tar.gz", hash = "sha256:1169d376c297e7de388d18b4481760d478b0e99a777cad3a9c86e556f4b697cb"},
+]
+
+[[package]]
+name = "tiktoken"
+version = "0.9.0"
+requires_python = ">=3.9"
+summary = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
+groups = ["default"]
+dependencies = [
+    "regex>=2022.1.18",
+    "requests>=2.26.0",
+]
+files = [
+    {file = "tiktoken-0.9.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:586c16358138b96ea804c034b8acf3f5d3f0258bd2bc3b0227af4af5d622e382"},
+    {file = "tiktoken-0.9.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d9c59ccc528c6c5dd51820b3474402f69d9a9e1d656226848ad68a8d5b2e5108"},
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+    {file = "tiktoken-0.9.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:b2a21133be05dc116b1d0372af051cd2c6aa1d2188250c9b553f9fa49301b336"},
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+    {file = "tiktoken-0.9.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cc156cb314119a8bb9748257a2eaebd5cc0753b6cb491d26694ed42fc7cb3139"},
+    {file = "tiktoken-0.9.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:cd69372e8c9dd761f0ab873112aba55a0e3e506332dd9f7522ca466e817b1b7a"},
+    {file = "tiktoken-0.9.0-cp313-cp313-win_amd64.whl", hash = "sha256:5ea0edb6f83dc56d794723286215918c1cde03712cbbafa0348b33448faf5b95"},
+    {file = "tiktoken-0.9.0.tar.gz", hash = "sha256:d02a5ca6a938e0490e1ff957bc48c8b078c88cb83977be1625b1fd8aac792c5d"},
+]
+
 [[package]]
 name = "tomli"
 version = "2.2.1"
@@ -3250,6 +3631,21 @@ files = [
     {file = "typing_extensions-4.13.2.tar.gz", hash = "sha256:e6c81219bd689f51865d9e372991c540bda33a0379d5573cddb9a3a23f7caaef"},
 ]
 
+[[package]]
+name = "typing-inspect"
+version = "0.9.0"
+summary = "Runtime inspection utilities for typing module."
+groups = ["default"]
+dependencies = [
+    "mypy-extensions>=0.3.0",
+    "typing-extensions>=3.7.4",
+    "typing>=3.7.4; python_version < \"3.5\"",
+]
+files = [
+    {file = "typing_inspect-0.9.0-py3-none-any.whl", hash = "sha256:9ee6fc59062311ef8547596ab6b955e1b8aa46242d854bfc78f4f6b0eff35f9f"},
+    {file = "typing_inspect-0.9.0.tar.gz", hash = "sha256:b23fc42ff6f6ef6954e4852c1fb512cdd18dbea03134f91f856a95ccc9461f78"},
+]
+
 [[package]]
 name = "typing-inspection"
 version = "0.4.0"
diff --git a/pyproject.toml b/pyproject.toml
index b66dc43..4a7ad8b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -41,6 +41,9 @@ dependencies = [
     "apscheduler>=3.11.0",
     "playwright>=1.52.0",
     "camoufox>=0.4.11",
+    "langchain>=0.3.25",
+    "langchain-openai>=0.3.17",
+    "langchain-community>=0.3.24",
     "html2text>=2025.4.15",
     "proxy-py>=2.4.10",
 ]
diff --git a/src/components/pages/chat/chat.tsx b/src/components/pages/chat/chat.tsx
index a41f1f6..05e5a90 100644
--- a/src/components/pages/chat/chat.tsx
+++ b/src/components/pages/chat/chat.tsx
@@ -343,7 +343,7 @@ export const AI: React.FC = () => {
               boxShadow: "0 4px 8px rgba(0, 0, 0, 0.2)",
             }}
           >
-            Must set either OPENAI_KEY or OLLAMA_MODEL to use AI features.
+            Must set either OPENAI_API_KEY or OLLAMA_MODEL to use AI features.
           </h4>
         </Box>
       )}