[bug] update broken packages in embedchain

.github/workflows/ci.yml

@@ -46,6 +46,8 @@ jobs:
           python-version: ${{ matrix.python-version }}
       - name: Install Hatch
         run: pip install hatch
+      - name: Install Poetry
+        run: pipx install poetry
       - name: Load cached venv
         id: cached-hatch-dependencies
         uses: actions/cache@v3

embedchain/embedchain/helpers/callbacks.py

@@ -2,7 +2,7 @@
 from typing import Any, Union
 
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
-from langchain.schema import LLMResult
+from langchain_core.outputs import LLMResult
 
 STOP_ITEM = "[END]"
 """

embedchain/embedchain/llm/base.py

@@ -3,7 +3,7 @@
 from collections.abc import Generator
 from typing import Any, Optional
 
-from langchain.schema import BaseMessage as LCBaseMessage
+from langchain_core.messages import BaseMessage as LCBaseMessage
 
 from embedchain.config import BaseLlmConfig
 from embedchain.config.llm.base import (
@@ -341,7 +341,7 @@ def _get_messages(prompt: str, system_prompt: Optional[str] = None) -> list[LCBa
         :return: List of messages
         :rtype: list[BaseMessage]
         """
-        from langchain.schema import HumanMessage, SystemMessage
+        from langchain_core.messages import HumanMessage, SystemMessage
 
         messages = []
         if system_prompt:

embedchain/embedchain/llm/groq.py

@@ -2,7 +2,7 @@
 from typing import Any, Optional
 
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
-from langchain.schema import HumanMessage, SystemMessage
+from langchain_core.messages import HumanMessage, SystemMessage
 
 try:
     from langchain_groq import ChatGroq

embedchain/embedchain/llm/jina.py

@@ -1,7 +1,7 @@
 import os
 from typing import Optional
 
-from langchain.schema import HumanMessage, SystemMessage
+from langchain_core.messages import HumanMessage, SystemMessage
 from langchain_community.chat_models import JinaChat
 
 from embedchain.config import BaseLlmConfig

embedchain/embedchain/llm/openai.py

@@ -4,7 +4,7 @@
 from typing import Any, Callable, Dict, Optional, Type, Union
 
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
-from langchain.schema import BaseMessage, HumanMessage, SystemMessage
+from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage
 from langchain_core.tools import BaseTool
 from langchain_openai import ChatOpenAI
 from pydantic import BaseModel

embedchain/pyproject.toml

@@ -102,7 +102,7 @@ chromadb = "^0.5.10"
 posthog = "^3.0.2"
 rich = "^13.7.0"
 beautifulsoup4 = "^4.12.2"
-pypdf = "^5.0.0"
+pypdf = "^6.0.0"
 gptcache = "^0.1.43"
 pysbd = "^0.3.4"
 mem0ai = "^0.1.54"
@@ -186,4 +186,4 @@ aws = ["langchain-aws"]
 [tool.poetry.group.docs.dependencies]
 
 [tool.poetry.scripts]
-ec = "embedchain.cli:cli"
+ec = "embedchain.cli:cli"

embedchain/tests/llm/test_anthrophic.py

@@ -2,7 +2,7 @@
 from unittest.mock import patch
 
 import pytest
-from langchain.schema import HumanMessage, SystemMessage
+from langchain_core.messages import HumanMessage, SystemMessage
 
 from embedchain.config import BaseLlmConfig
 from embedchain.llm.anthropic import AnthropicLlm

embedchain/tests/llm/test_azure_openai.py

@@ -2,7 +2,7 @@
 
 import httpx
 import pytest
-from langchain.schema import HumanMessage, SystemMessage
+from langchain_core.messages import HumanMessage, SystemMessage
 
 from embedchain.config import BaseLlmConfig
 from embedchain.llm.azure_openai import AzureOpenAILlm

embedchain/tests/llm/test_vertex_ai.py

@@ -1,7 +1,7 @@
 from unittest.mock import MagicMock, patch
 
 import pytest
-from langchain.schema import HumanMessage, SystemMessage
+from langchain_core.messages import HumanMessage, SystemMessage
 
 from embedchain.config import BaseLlmConfig
 from embedchain.core.db.database import database_manager

embedchain/tests/loaders/test_pdf_file.py

@@ -1,5 +1,5 @@
 import pytest
-from langchain.schema import Document
+from langchain_core.documents import Document
 
 
 def test_load_data(loader, mocker):

examples/misc/personalized_search.py

@@ -9,7 +9,7 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_openai import ChatOpenAI
 from langchain_tavily import TavilySearch
-from langchain.schema import HumanMessage
+from langchain_core.messages import HumanMessage
 from datetime import datetime
 import logging
 

mem0/vector_stores/azure_ai_search.py

@@ -222,7 +222,7 @@ def search(self, query, vectors, limit=5, filters=None):
         if filters:
             filter_expression = self._build_filter_expression(filters)
 
-        vector_query = VectorizedQuery(vector=vectors, k_nearest_neighbors=limit, fields="vector")
+        vector_query = VectorizedQuery(vector=vectors, k_nearest_neighbors_count=limit, fields=["vector"])
         if self.hybrid_search:
             search_results = self.search_client.search(
                 search_text=query,

mem0/vector_stores/vertex_ai_vector_search.py

@@ -12,7 +12,7 @@
 try:
     from langchain_core.documents import Document
 except ImportError:  # pragma: no cover - fallback for older LangChain versions
-    from langchain.schema import Document  # type: ignore[no-redef]
+    from langchain_core.documents import Document  # type: ignore[no-redef]
 
 from mem0.configs.vector_stores.vertex_ai_vector_search import (
     GoogleMatchingEngineConfig,

tests/vector_stores/test_azure_ai_search.py

@@ -542,7 +542,7 @@ def test_search_basic(azure_ai_search_instance):
     # Check parameters
     assert len(kwargs["vector_queries"]) == 1
     assert kwargs["vector_queries"][0].vector == query_vector
-    assert kwargs["vector_queries"][0].k_nearest_neighbors == 5
+    assert kwargs["vector_queries"][0].k_nearest_neighbors_count == 5
     assert kwargs["vector_queries"][0].fields == "vector"
     assert kwargs["filter"] is None  # No filters
     assert kwargs["top"] == 5