Bump langchain/langgraph deps

backend/chatbot.py

@@ -92,7 +92,9 @@ def parse_output(output: list) -> tuple[str, list[str], list[str]]:
         logging.error(f"Output is not a list: {type(output)}")
         return fail_msg, [], []
     if len(output) < MIN_OUTPUT_LENGTH:
-        logging.error(f"Output too short: {len(output)} elements (expected >= {MIN_OUTPUT_LENGTH})")
+        logging.error(
+            f"Output too short: {len(output)} elements (expected >= {MIN_OUTPUT_LENGTH})"
+        )
         return fail_msg, [], []
 
     # Validate last element contains generation
@@ -106,7 +108,9 @@ def parse_output(output: list) -> tuple[str, list[str], list[str]]:
     key = "rag_generate" if is_rag else "generate"
 
     if key not in last:
-        logging.error(f"Missing '{key}' key in final output. Available keys: {list(last.keys())}")
+        logging.error(
+            f"Missing '{key}' key in final output. Available keys: {list(last.keys())}"
+        )
         return fail_msg, [], []
 
     if "messages" not in last[key]:
@@ -261,12 +265,16 @@ def main() -> None:
         console.print("\n[yellow]Interrupted. Goodbye![/yellow]")
     except ValueError as e:
         console.print(f"[bold red]Configuration Error:[/bold red] {str(e)}")
-        console.print("[yellow]Check your environment variables and try again.[/yellow]")
+        console.print(
+            "[yellow]Check your environment variables and try again.[/yellow]"
+        )
         if debug:
             logging.exception("Configuration error")
     except ConnectionError as e:
         console.print(f"[bold red]Connection Error:[/bold red] {str(e)}")
-        console.print("[yellow]Check your network connection and database availability.[/yellow]")
+        console.print(
+            "[yellow]Check your network connection and database availability.[/yellow]"
+        )
         if debug:
             logging.exception("Connection error")
     except Exception as e:

backend/pyproject.toml

@@ -13,15 +13,15 @@ dependencies = [
     "google-cloud-storage>=2.19.0",
     "httpx>=0.28.1",
     "huggingface-hub[cli]==0.34.4",
-    "langchain==0.3.27",
-    "langchain-community==0.3.27",
-    "langchain-google-genai==2.1.9",
-    "langchain-google-vertexai==2.0.28",
-    "langchain-huggingface==0.3.1",
+    "langchain>=1.2.12",
+    "langchain-community>=0.4.1",
+    "langchain-google-genai>=4.2.1",
+    "langchain-google-vertexai>=3.2.2",
+    "langchain-huggingface>=1.2.1",
     "langchain-mcp-adapters>=0.1.9",
-    "langchain-ollama==0.3.6",
-    "langgraph>=0.7.0",
-    "langgraph-checkpoint>=3.0.0",
+    "langchain-ollama>=1.0.1",
+    "langgraph>=1.1.0",
+    "langgraph-checkpoint>=4.0.0",
     "markdown==3.8.2",
     "myst-parser==4.0.1",
     "nest-asyncio>=1.6.0",

backend/src/agents/retriever_graph.py

@@ -4,7 +4,7 @@
 
 from langgraph.graph import START, StateGraph
 from langgraph.graph.state import CompiledStateGraph
-from langchain.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
 from langchain_google_vertexai import ChatVertexAI
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_ollama import ChatOllama

backend/src/agents/retriever_mcp.py

@@ -4,7 +4,7 @@
 from ..openroad_mcp.client.client import get_tools
 from langgraph.graph import END
 from .retriever_typing import AgentState
-from langchain.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.tools.base import ToolException
 from langchain_google_vertexai import ChatVertexAI
 from langchain_google_genai import ChatGoogleGenerativeAI

backend/src/agents/retriever_rag.py

@@ -3,9 +3,9 @@
 from langchain_core.messages import AnyMessage
 from langgraph.graph import END
 from langchain_core.tools import BaseTool
-from langchain.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.output_parsers import JsonOutputParser
-from langchain.tools.render import render_text_description
+from langchain_core.tools.render import render_text_description
 from langchain_google_vertexai import ChatVertexAI
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_ollama import ChatOllama

backend/src/agents/retriever_tools.py

@@ -3,8 +3,8 @@
 from dotenv import load_dotenv
 
 from langchain_core.tools import tool
-from langchain.retrievers import EnsembleRetriever
-from langchain.retrievers import ContextualCompressionRetriever
+from langchain_classic.retrievers import EnsembleRetriever
+from langchain_classic.retrievers import ContextualCompressionRetriever
 
 from ..chains.hybrid_retriever_chain import HybridRetrieverChain
 from ..tools.format_docs import format_docs

backend/src/chains/base_chain.py

@@ -1,6 +1,6 @@
 from typing import Optional, Union, Any
 
-from langchain.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from langchain_google_vertexai import ChatVertexAI
 from langchain_google_genai import ChatGoogleGenerativeAI

backend/src/chains/bm25_retriever_chain.py

@@ -2,7 +2,7 @@
 
 from langchain_community.retrievers import BM25Retriever
 from langchain_core.vectorstores import VectorStoreRetriever
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 from langchain_google_vertexai import ChatVertexAI
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_ollama import ChatOllama

backend/src/chains/hybrid_retriever_chain.py

@@ -1,16 +1,14 @@
 import os
 from typing import Optional, Union, Any
 
-from langchain.retrievers import EnsembleRetriever
-from langchain.retrievers import ContextualCompressionRetriever
+from langchain_classic.retrievers import EnsembleRetriever
+from langchain_classic.retrievers import ContextualCompressionRetriever
 from langchain_core.runnables import RunnableParallel, RunnablePassthrough
 from langchain_community.cross_encoders import HuggingFaceCrossEncoder
 from langchain_google_vertexai import ChatVertexAI
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_ollama import ChatOllama
-from langchain.retrievers.document_compressors.cross_encoder_rerank import (
-    CrossEncoderReranker,
-)
+from langchain_classic.retrievers.document_compressors import CrossEncoderReranker
 
 from .base_chain import BaseChain
 from .similarity_retriever_chain import SimilarityRetrieverChain

backend/src/chains/multi_retriever_chain.py

@@ -4,7 +4,7 @@
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_ollama import ChatOllama
 from langchain_core.runnables import RunnableParallel, RunnablePassthrough
-from langchain.retrievers import EnsembleRetriever
+from langchain_classic.retrievers import EnsembleRetriever
 
 from .base_chain import BaseChain
 from .similarity_retriever_chain import SimilarityRetrieverChain

backend/src/chains/similarity_retriever_chain.py

@@ -2,7 +2,7 @@
 from typing import Optional, Tuple, Any, Union
 
 from langchain_core.runnables import RunnableParallel, RunnablePassthrough
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 from langchain_google_vertexai import ChatVertexAI
 from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_ollama import ChatOllama

backend/src/openroad_mcp/server/orfs/orfs_make.py

@@ -1,6 +1,6 @@
 import logging
 from src.openroad_mcp.server.orfs.orfs_tools import ORFS
-from langchain.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.output_parsers import JsonOutputParser
 from src.prompts.prompt_templates import env_prompt_template
 

backend/src/tools/chunk_documents.py

@@ -1,5 +1,5 @@
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.docstore.document import Document
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langchain_core.documents import Document
 
 
 def chunk_documents(

backend/src/tools/format_docs.py

@@ -1,4 +1,4 @@
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 
 from ..prompts.prompt_templates import gh_discussion_prompt_template
 

backend/src/tools/process_html.py

@@ -5,7 +5,7 @@
 from tqdm import tqdm
 from typing import Optional
 
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 from langchain_community.document_loaders import UnstructuredHTMLLoader
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 

backend/src/tools/process_json.py

@@ -3,7 +3,7 @@
 import logging
 from typing import Any
 
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 
 logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO").upper())
 

backend/src/tools/process_md.py

@@ -7,7 +7,7 @@
 from bs4 import BeautifulSoup
 from typing import Optional
 
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 from .chunk_documents import chunk_documents
 

backend/src/tools/process_pdf.py

@@ -4,7 +4,7 @@
 from dotenv import load_dotenv
 from pypdf.errors import PdfStreamError
 
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 from langchain_community.document_loaders import PyPDFLoader
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 

backend/src/vectorstores/faiss.py

@@ -8,7 +8,7 @@
 from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_google_genai import GoogleGenerativeAIEmbeddings
 from langchain_google_vertexai import VertexAIEmbeddings
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 
 from ..tools.process_md import process_md
 from ..tools.process_pdf import process_pdf_docs
@@ -45,9 +45,7 @@ def __init__(
             logging.info("Using Google GenerativeAI embeddings...")
 
         elif embeddings_type == "GOOGLE_VERTEXAI":
-            self.embedding_model = VertexAIEmbeddings(
-                model_name=self.embeddings_model_name
-            )
+            self.embedding_model = VertexAIEmbeddings(model=self.embeddings_model_name)
             logging.info("Using Google VertexAI embeddings...")
 
         elif embeddings_type == "HF":

backend/tests/test_base_chain.py

@@ -1,6 +1,6 @@
 import pytest
 from unittest.mock import Mock
-from langchain.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
 
 from src.chains.base_chain import BaseChain
 

backend/tests/test_bm25_retriever_chain.py

@@ -1,6 +1,6 @@
 import pytest
 from unittest.mock import Mock, patch
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 
 from src.chains.bm25_retriever_chain import BM25RetrieverChain
 

backend/tests/test_chunk_documents.py

@@ -1,5 +1,5 @@
 import pytest
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 
 from src.tools.chunk_documents import chunk_documents
 

backend/tests/test_faiss_vectorstore.py

@@ -3,7 +3,7 @@
 from unittest.mock import Mock, patch
 
 from langchain_community.vectorstores.utils import DistanceStrategy
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 
 from src.vectorstores.faiss import FAISSVectorDatabase
 
@@ -55,7 +55,7 @@ def test_init_with_google_vertexai_embeddings(self):
             )
 
             assert db.embeddings_model_name == "textembedding-gecko@001"
-            mock_vertex.assert_called_once_with(model_name="textembedding-gecko@001")
+            mock_vertex.assert_called_once_with(model="textembedding-gecko@001")
 
     def test_init_with_invalid_embeddings_type(self):
         """Test initialization with invalid embeddings type raises error."""

backend/tests/test_format_docs.py

@@ -1,5 +1,5 @@
 import pytest
-from langchain.docstore.document import Document
+from langchain_core.documents import Document
 
 from src.tools.format_docs import format_docs, CHUNK_SEPARATOR
 

backend/tests/test_process_md.py

@@ -1,5 +1,6 @@
 import pytest
 from unittest.mock import patch
+from langchain_core.documents import Document
 
 from src.tools.process_md import md_to_text
 
@@ -263,8 +264,6 @@ def test_process_md_without_splitting(
             '{"test.md": "https://example.com"}'
         )
 
-        from langchain.docstore.document import Document
-
         mock_docs = [
             Document(page_content="Test content", metadata={"source": "test.md"})
         ]
@@ -300,8 +299,6 @@ def test_process_md_with_splitting(
             '{"test.md": "https://example.com"}'
         )
 
-        from langchain.docstore.document import Document
-
         mock_doc = Document(page_content="Test content", metadata={"source": "test.md"})
         mock_load_docs.return_value = [mock_doc]
         mock_split.return_value = [mock_doc]
@@ -343,8 +340,6 @@ def test_process_md_missing_source_in_dict(
             "{}"  # Empty JSON
         )
 
-        from langchain.docstore.document import Document
-
         mock_docs = [
             Document(page_content="Test content", metadata={"source": "missing.md"})
         ]
@@ -388,8 +383,6 @@ def test_process_md_logs_warning_for_missing_source(
         mock_listdir.return_value = ["file.md"]
         mock_open.return_value.__enter__.return_value.read.return_value = "{}"
 
-        from langchain.docstore.document import Document
-
         mock_docs = [
             Document(page_content="Test content", metadata={"source": "missing.md"})
         ]
@@ -414,8 +407,6 @@ def test_process_md_realistic_workflow(
         mock_listdir.return_value = ["installation.md", "usage.md"]
         mock_open.return_value.__enter__.return_value.read.return_value = '{"installation.md": "https://docs.example.com/install", "usage.md": "https://docs.example.com/usage"}'
 
-        from langchain.docstore.document import Document
-
         mock_docs = [
             Document(
                 page_content="Installation content",