benchmarks[major]: bump core to 0.3 (#211)

- Drop support for python 3.8
- Bump langchain-core to 0.3
- Update pydantic objects to v2

.github/workflows/_pydantic_compatibility.yml

@@ -1,94 +0,0 @@
-name: pydantic v1/v2 compatibility
-
-on:
-  workflow_call:
-    inputs:
-      working-directory:
-        required: true
-        type: string
-        description: "From which folder this pipeline executes"
-
-env:
-  POETRY_VERSION: "1.6.1"
-
-jobs:
-  build:
-    timeout-minutes: 5
-    defaults:
-      run:
-        working-directory: ${{ inputs.working-directory }}
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version:
-          - "3.8"
-          - "3.9"
-          - "3.10"
-          - "3.11"
-    name: Pydantic v1/v2 compatibility - Python ${{ matrix.python-version }}
-    steps:
-      - uses: actions/checkout@v3
-
-      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
-        with:
-          python-version: ${{ matrix.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: pydantic-cross-compat
-
-      - name: Install dependencies
-        shell: bash
-        run: poetry install --with test
-
-      - name: Install the opposite major version of pydantic
-        # If normal tests use pydantic v1, here we'll use v2, and vice versa.
-        shell: bash
-        run: |
-          # Determine the major part of pydantic version
-          REGULAR_VERSION=$(poetry run python -c "import pydantic; print(pydantic.__version__)" | cut -d. -f1)
-
-          if [[ "$REGULAR_VERSION" == "1" ]]; then
-            PYDANTIC_DEP=">=2.1,<3"
-            TEST_WITH_VERSION="2"
-          elif [[ "$REGULAR_VERSION" == "2" ]]; then
-            PYDANTIC_DEP="<2"
-            TEST_WITH_VERSION="1"
-          else
-            echo "Unexpected pydantic major version '$REGULAR_VERSION', cannot determine which version to use for cross-compatibility test."
-            exit 1
-          fi
-
-          # Install via `pip` instead of `poetry add` to avoid changing lockfile,
-          # which would prevent caching from working: the cache would get saved
-          # to a different key than where it gets loaded from.
-          poetry run pip install "pydantic${PYDANTIC_DEP}"
-
-          # Ensure that the correct pydantic is installed now.
-          echo "Checking pydantic version... Expecting ${TEST_WITH_VERSION}"
-
-          # Determine the major part of pydantic version
-          CURRENT_VERSION=$(poetry run python -c "import pydantic; print(pydantic.__version__)" | cut -d. -f1)
-
-          # Check that the major part of pydantic version is as expected, if not
-          # raise an error
-          if [[ "$CURRENT_VERSION" != "$TEST_WITH_VERSION" ]]; then
-            echo "Error: expected pydantic version ${CURRENT_VERSION} to have been installed, but found: ${TEST_WITH_VERSION}"
-            exit 1
-          fi
-          echo "Found pydantic version ${CURRENT_VERSION}, as expected"
-      - name: Run pydantic compatibility tests
-        shell: bash
-        run: make test
-
-      - name: Ensure the tests did not create any additional files
-        shell: bash
-        run: |
-          set -eu
-
-          STATUS="$(git status)"
-          echo "$STATUS"
-
-          # grep will exit non-zero if the target message isn't found,
-          # and `set -e` above will cause the step to fail.
-          echo "$STATUS" | grep 'nothing to commit, working tree clean'

.github/workflows/ci.yml

@@ -31,12 +31,6 @@ jobs:
       working-directory: .
     secrets: inherit
 
-  pydantic-compatibility:
-    uses:
-      ./.github/workflows/_pydantic_compatibility.yml
-    with:
-      working-directory: .
-    secrets: inherit
   test:
     timeout-minutes: 5
     runs-on: ubuntu-latest

.github/workflows/tool_benchmarks.yml

@@ -5,6 +5,12 @@ on:
   schedule:
     - cron: '0 0 * * 0'  # Runs at midnight (00:00) every Sunday (UTC time)
 
+env:
+  POETRY_VERSION: "1.6.1"
+  LANGCHAIN_API_KEY: ${{ secrets.LANGCHAIN_API_KEY }}
+  OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+  ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
+
 jobs:
   run_tool_benchmarks:
     runs-on: ubuntu-latest
@@ -27,7 +33,12 @@ jobs:
           poetry install --with test,lint,typing,docs
 
       - name: Multiverse math benchmark
-        run: python scripts/multiverse_math_benchmark.py
+
+        run: |
+          cd scripts
+          poetry run python multiverse_math_benchmark.py
       
       - name: Query analysis benchmark
-        run: python scripts/query_analysis_benchmark.py
+        run: |
+          cd scripts
+          poetry run python query_analysis_benchmark.py

README.md

@@ -43,7 +43,7 @@ Explore Agent Traces on LangSmith:
 * [Relational Data](https://smith.langchain.com/public/22721064-dcf6-4e42-be65-e7c46e6835e7/d)
 * [Tool Usage (1-tool)](https://smith.langchain.com/public/ac23cb40-e392-471f-b129-a893a77b6f62/d)
 * [Tool Usage (26-tools)](https://smith.langchain.com/public/366bddca-62b3-4b6e-849b-a478abab73db/d)
-* [Mutiverse Math](https://smith.langchain.com/public/983faff2-54b9-4875-9bf2-c16913e7d489/d)
+* [Multiverse Math](https://smith.langchain.com/public/983faff2-54b9-4875-9bf2-c16913e7d489/d)
 
 ## Installation
 

archived/csv-qa/custom_agent.py

@@ -3,12 +3,12 @@ from langchain.agents import AgentExecutor, OpenAIFunctionsAgent
 from langchain.agents.agent_toolkits.conversational_retrieval.tool import (
     create_retriever_tool,
 )
-from langchain.chat_models import ChatOpenAI
 from langchain.embeddings import OpenAIEmbeddings
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain.smith import RunEvalConfig, run_on_dataset
 from langchain.tools import PythonAstREPLTool
 from langchain.vectorstores import FAISS
+from langchain_openai import ChatOpenAI
 from langsmith import Client
 from pydantic import BaseModel, Field
 

archived/csv-qa/pandas_agent_gpt_35.py

@@ -1,8 +1,8 @@
 import pandas as pd
 from langchain.agents.agent_toolkits import create_pandas_dataframe_agent
 from langchain.agents.agent_types import AgentType
-from langchain.chat_models import ChatOpenAI
 from langchain.smith import RunEvalConfig, run_on_dataset
+from langchain_openai import ChatOpenAI
 from langsmith import Client
 
 if __name__ == "__main__":

archived/csv-qa/pandas_agent_gpt_4.py

@@ -1,8 +1,8 @@
 import pandas as pd
 from langchain.agents.agent_toolkits import create_pandas_dataframe_agent
 from langchain.agents.agent_types import AgentType
-from langchain.chat_models import ChatOpenAI
 from langchain.smith import RunEvalConfig, run_on_dataset
+from langchain_openai import ChatOpenAI
 from langsmith import Client
 
 if __name__ == "__main__":

archived/csv-qa/pandas_ai.py

@@ -1,8 +1,8 @@
 import pandas as pd
-from langchain.chat_models import ChatOpenAI
 from langchain.prompts import ChatPromptTemplate
 from langchain.schema.output_parser import StrOutputParser
 from langchain.smith import RunEvalConfig, run_on_dataset
+from langchain_openai import ChatOpenAI
 from langsmith import Client
 from pandasai import PandasAI
 

archived/csv-qa/streamlit_app.py

@@ -2,7 +2,7 @@ import pandas as pd
 import streamlit as st
 from langchain.agents.agent_toolkits import create_pandas_dataframe_agent
 from langchain.agents.agent_types import AgentType
-from langchain.chat_models import ChatOpenAI
+from langchain_openai import ChatOpenAI
 
 df = pd.read_csv("titanic.csv")
 

archived/extraction/streamlit_app.py

@@ -1,6 +1,6 @@
 import streamlit as st
 from langchain.chains import create_extraction_chain
-from langchain.chat_models import ChatOpenAI
+from langchain_openai import ChatOpenAI
 from langsmith import Client
 
 st.set_page_config(page_title="🦜🔗 Text-to-graph extraction")

archived/langchain-docs-benchmarking/packages/anthropic-iterative-search/anthropic_iterative_search/chain.py

@@ -1,8 +1,8 @@
 from langchain.chat_models import ChatAnthropic
 from langchain.prompts import ChatPromptTemplate
-from langchain.pydantic_v1 import BaseModel
 from langchain.schema.output_parser import StrOutputParser
 from langchain.schema.runnable import RunnableLambda
+from pydantic import BaseModel
 
 from .prompts import answer_prompt
 from .retriever_agent import executor

archived/langchain-docs-benchmarking/packages/openai-functions-agent/openai_functions_agent/agent.py

@@ -3,13 +3,13 @@ from typing import List, Tuple
 from langchain.agents import AgentExecutor
 from langchain.agents.format_scratchpad import format_to_openai_functions
 from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser
-from langchain.chat_models import ChatOpenAI
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
-from langchain.pydantic_v1 import BaseModel, Field
 from langchain.schema.messages import AIMessage, HumanMessage
 from langchain.tools import tool
 from langchain.tools.render import format_tool_to_openai_function
 from langchain_docs_retriever.retriever import get_retriever
+from langchain_openai import ChatOpenAI
+from pydantic import BaseModel, Field
 
 # This is used to tell the model how to best use the retriever.
 

archived/langchain-docs-benchmarking/run_evals.py

@@ -7,9 +7,9 @@ from typing import Callable, Optional
 
 from anthropic_iterative_search.chain import chain as anthropic_agent_chain
 from chat_langchain.chain import create_chain
-from langchain.chat_models import ChatOpenAI
 from langchain.schema.runnable import Runnable
 from langchain.smith import RunEvalConfig, run_on_dataset
+from langchain_openai import ChatOpenAI
 from langsmith import Client
 from oai_assistant.chain import agent_executor as openai_assistant_chain
 from openai_functions_agent import agent_executor as openai_functions_agent_chain

docs/source/notebooks/extraction/chat_extraction.ipynb

@@ -259,8 +259,8 @@
    },
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.output_parsers.openai_functions import JsonOutputFunctionsParser\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "llm = ChatOpenAI(model=\"gpt-4-1106-preview\", temperature=0).bind_functions(\n",
     "    functions=[task.schema],\n",

docs/source/notebooks/extraction/email.ipynb

@@ -232,8 +232,8 @@
    },
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.output_parsers.openai_functions import JsonOutputFunctionsParser\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "llm = ChatOpenAI(model=\"gpt-3.5-turbo-16k\", temperature=0).bind_functions(\n",
     "    functions=[task.schema],\n",

docs/source/notebooks/extraction/intro.ipynb

@@ -97,7 +97,7 @@
    },
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "from langchain_benchmarks.extraction import get_eval_config\n",
     "\n",

docs/source/notebooks/retrieval/comparing_techniques.ipynb

@@ -75,6 +75,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "7fb27b941602401d91542211134fc71a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -728,12 +729,12 @@
     "from langchain.agents import AgentExecutor\n",
     "from langchain.agents.format_scratchpad import format_to_openai_functions\n",
     "from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser\n",
-    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
     "from langchain.pydantic_v1 import BaseModel, Field\n",
     "from langchain.schema.messages import AIMessage, HumanMessage\n",
     "from langchain.tools import tool\n",
     "from langchain.tools.render import format_tool_to_openai_function\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "# This is used to tell the model how to best use the retriever.\n",
     "\n",

docs/source/notebooks/retrieval/multi_modal_benchmarking/multi_modal_eval.ipynb

@@ -508,8 +508,8 @@
    },
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.schema.messages import HumanMessage\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "\n",
     "def image_summarize(img_base64, prompt):\n",

docs/source/notebooks/retrieval/multi_modal_benchmarking/multi_modal_eval_baseline.ipynb

@@ -328,10 +328,10 @@
    },
    "outputs": [],
    "source": [
-    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
     "from langchain.schema.output_parser import StrOutputParser\n",
     "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "\n",
     "def rag_chain(retriever):\n",

docs/source/notebooks/retrieval/semi_structured_benchmarking/semi_structured.ipynb

@@ -451,11 +451,11 @@
    "source": [
     "from operator import itemgetter\n",
     "\n",
-    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import ChatPromptTemplate\n",
     "from langchain.schema.document import Document\n",
     "from langchain.schema.output_parser import StrOutputParser\n",
     "from langchain.schema.runnable.passthrough import RunnableAssign\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "# Prompt\n",
     "prompt = ChatPromptTemplate.from_messages(\n",

docs/source/notebooks/retrieval/semi_structured_benchmarking/ss_eval_multi_vector.ipynb

@@ -126,7 +126,6 @@
    "source": [
     "import uuid\n",
     "\n",
-    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.document_loaders import PyPDFLoader\n",
     "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.prompts import ChatPromptTemplate\n",
@@ -138,6 +137,7 @@
     "from langchain.storage import InMemoryStore\n",
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
     "from langchain.vectorstores import Chroma\n",
+    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "\n",
     "def prepare_documents(docs):\n",

langchain_benchmarks/extraction/evaluators.py

@@ -1,8 +1,8 @@
 from typing import Optional
 
-from langchain.chat_models import ChatOpenAI
 from langchain.chat_models.base import BaseChatModel
 from langchain.smith import RunEvalConfig
+from langchain_openai import ChatOpenAI
 
 
 def get_eval_config(eval_llm: Optional[BaseChatModel] = None) -> RunEvalConfig:

langchain_benchmarks/extraction/implementations.py

@@ -2,10 +2,10 @@
 from typing import Any, Dict, List, Optional, Type
 
 from langchain.chains.openai_functions import convert_to_openai_function
-from langchain.chat_models import ChatOpenAI
 from langchain.output_parsers.openai_functions import JsonOutputFunctionsParser
 from langchain.prompts import ChatPromptTemplate
 from langchain.schema.runnable import Runnable
+from langchain_openai import ChatOpenAI
 from langsmith.client import Client
 from pydantic import BaseModel
 

langchain_benchmarks/extraction/tasks/chat_extraction/schema.py

@@ -1,7 +1,7 @@
 from enum import Enum
 from typing import List, Optional
 
-from langchain.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 
 
 class QuestionCategory(str, Enum):

langchain_benchmarks/extraction/tasks/email_task.py

@@ -2,7 +2,7 @@ from enum import Enum
 from typing import List, Optional
 
 from langchain.prompts import ChatPromptTemplate
-from langchain.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 
 from langchain_benchmarks.schema import ExtractionTask
 

langchain_benchmarks/extraction/tasks/high_cardinality/name_correction.py

@@ -1,7 +1,7 @@
 from langchain.smith import RunEvalConfig
-from langchain_core.pydantic_v1 import BaseModel, Field
 from langsmith.evaluation import EvaluationResult, run_evaluator
 from langsmith.schemas import Example, Run
+from pydantic import BaseModel, Field
 
 from langchain_benchmarks.schema import ExtractionTask
 

langchain_benchmarks/rag/evaluators.py

@@ -1,8 +1,8 @@
 from typing import Optional
 
-from langchain.chat_models import ChatOpenAI
 from langchain.evaluation import load_evaluator
 from langchain.smith import RunEvalConfig
+from langchain_openai import ChatOpenAI
 
 try:
     from langchain.schema.language_model import BaseLanguageModel

langchain_benchmarks/rag/tasks/langchain_docs/architectures/chain_registry.py

@@ -1,9 +1,9 @@
 from typing import Optional
 
 from langchain.base_language import BaseLanguageModel
-from langchain.chat_models import ChatOpenAI
 from langchain.schema.retriever import BaseRetriever
 from langchain.schema.runnable import Runnable
+from langchain_openai import ChatOpenAI
 
 from langchain_benchmarks.rag.tasks.langchain_docs.architectures.crqa import (
     create_response_chain,

langchain_benchmarks/rag/utils/indexing.py

@@ -3,11 +3,9 @@ import os
 from functools import partial
 from typing import Callable, Iterable, List, Optional
 
-from langchain.chat_models import ChatOpenAI
 from langchain.indexes import SQLRecordManager, index
 from langchain.output_parsers.openai_functions import JsonKeyOutputFunctionsParser
 from langchain.prompts import ChatPromptTemplate
-from langchain.pydantic_v1 import BaseModel
 from langchain.retrievers.multi_vector import MultiVectorRetriever
 from langchain.retrievers.parent_document_retriever import ParentDocumentRetriever
 from langchain.schema.document import Document
@@ -18,6 +16,8 @@ from langchain.schema.storage import BaseStore
 from langchain.schema.vectorstore import VectorStore
 from langchain.storage import InMemoryStore
 from langchain.text_splitter import RecursiveCharacterTextSplitter, TextSplitter
+from langchain_openai import ChatOpenAI
+from pydantic import BaseModel
 from tqdm.auto import tqdm
 
 logger = logging.getLogger(__name__)

langchain_benchmarks/tool_usage/evaluators.py

@@ -10,11 +10,11 @@ from typing import Any, Literal, Optional, Union
 
 from langchain.callbacks.manager import collect_runs
 from langchain.chains import LLMChain
-from langchain.chat_models import ChatOpenAI
 from langchain.evaluation import EvaluatorType, StringEvaluator, load_evaluator
 from langchain.evaluation.schema import StringEvaluator
 from langchain.smith import RunEvalConfig
 from langchain_core.language_models import BaseChatModel, BaseLanguageModel
+from langchain_openai import ChatOpenAI
 from langsmith.evaluation.evaluator import (
     EvaluationResult,
     EvaluationResults,
@@ -175,7 +175,7 @@ class AgentTrajectoryEvaluator(RunEvaluator):
             eval_llm = eval_llm or ChatOpenAI(
                 model="gpt-4",
                 temperature=0,
-                model_kwargs={"seed": 42},
+                seed=42,
                 max_retries=1,
                 request_timeout=60,
             )

langchain_benchmarks/tool_usage/tasks/query_analysis.py

@@ -1,10 +1,10 @@
 from datetime import datetime
 from typing import List, Literal, Union, cast
 
-from langchain.pydantic_v1 import BaseModel, Field
 from langchain.tools import BaseTool, tool
 from langchain_core.messages import HumanMessage
 from langsmith.client import Client
+from pydantic import BaseModel, Field
 
 from langchain_benchmarks.schema import ToolUsageEnvironment, ToolUsageTask
 

pyproject.toml

@@ -1,49 +1,33 @@
 [tool.poetry]
 name = "langchain-benchmarks"
-version = "0.0.13"
+version = "0.0.15"
 description = "🦜💪 Flex those feathers!"
 authors = ["LangChain AI"]
 license = "MIT"
 readme = "README.md"
 
 [tool.poetry.dependencies]
-python = "^3.8.1"
-langchain = "^0.1.15"
+python = "^3.9"
+langchain = "^0.3"
+langchain-community = "^0.3"
+langchain-core= "^0.3.12"
 langsmith = ">=0.0.70"
 tqdm = "^4"
 ipywidgets = "^8"
 tabulate = ">=0.8.0"
+langchain-openai = "^0.2"
 
 [tool.poetry.group.dev]
 optional = true
 
 [tool.poetry.group.dev.dependencies]
 jupyter = "^1.0.0"
-langchain-core = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core"}
-langchain = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/langchain"}
-langchain-anthropic = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/anthropic"}
-langchain-google-vertexai= {git = "https://github.com/langchain-ai/langchain-google.git", subdirectory = "libs/vertexai/"}
-langchain-fireworks = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/fireworks"}
-langchain-mistralai = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/mistralai"}
-langchain-cohere = {git = "https://github.com/langchain-ai/langchain-cohere.git", subdirectory="libs/cohere"}
-langchain-groq = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/groq"}
-langchain-openai = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/openai"}
-
 
 [tool.poetry.group.typing]
 optional = true
 
 [tool.poetry.group.typing.dependencies]
 mypy = "^1.7.0"
-langchain-core = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core"}
-langchain = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/langchain"}
-langchain-anthropic = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/anthropic"}
-langchain-fireworks = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/fireworks"}
-langchain-mistralai = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/mistralai"}
-langchain-cohere = {git = "https://github.com/langchain-ai/langchain-cohere.git", subdirectory="libs/cohere"}
-langchain-groq = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/groq"}
-langchain-openai = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/openai"}
-
 [tool.poetry.group.lint]
 optional = true
 
@@ -74,14 +58,12 @@ pytest-socket = "^0.6.0"
 pytest-watch = "^4.2.0"
 pytest-timeout = "^2.2.0"
 freezegun = "^1.3.1"
-langchain-core = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core"}
-langchain = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/langchain"}
-langchain-anthropic = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/anthropic"}
-langchain-fireworks = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/fireworks"}
-langchain-mistralai = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/mistralai"}
-langchain-cohere = {git = "https://github.com/langchain-ai/langchain-cohere.git", subdirectory="libs/cohere"}
-langchain-groq = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/groq"}
-langchain-openai = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/openai"}
+langchain-anthropic = "^0.2"
+langchain-fireworks = "^0.2"
+langchain-mistralai = "^0.2"
+langchain-groq = "^0.2"
+langchain-core = "^0.3.12"
+faiss-cpu = ">=1.8.0"
 
 [tool.ruff]
 select = [