LangChain package version drift — langchain-openai, langchain-anthropic, langchain-google-genai conflicts

# ---------------------------------------
# pyproject.toml — pin every langchain-* package
# ---------------------------------------
[project]
name = "myapp"
requires-python = ">=3.11"

dependencies = [
    # Foundation — pin exact
    "langchain-core==0.3.28",
    "langchain==0.3.25",
    "langchain-community==0.3.15",

    # Provider integrations — pin exact
    "langchain-openai==0.2.19",
    "langchain-anthropic==0.2.10",
    "langchain-google-genai==2.0.9",

    # Vector store integration
    "langchain-chroma==0.1.4",

    # LangGraph if used
    "langgraph==0.2.62",

    # LangSmith for tracing (optional but recommended)
    "langsmith==0.2.11",

    # Pydantic — LangChain 0.3+ requires v2
    "pydantic>=2.5,<3.0",
]

# Coordinated upgrade — all langchain-* packages together
pip install --upgrade \
    langchain-core \
    langchain \
    langchain-community \
    langchain-openai \
    langchain-anthropic \
    langchain-google-genai \
    langchain-chroma \
    langgraph \
    langsmith

# Then re-lock
pip freeze | grep -E "^(langchain|langgraph|langsmith|pydantic)" > current_versions.txt
cat current_versions.txt

# Update pyproject.toml with the new pins, run your test suite,
# then commit both the pyproject.toml and the lockfile together.

"""Quick smoke test to verify LangChain package compatibility."""
import sys

def check_import(name: str):
    try:
        __import__(name)
        mod = sys.modules[name]
        version = getattr(mod, "__version__", None)
        print(f"✓ {name:35s} {version}")
        return True
    except ImportError as e:
        print(f"✗ {name:35s} ImportError: {e}")
        return False

packages_to_check = [
    "langchain_core",
    "langchain",
    "langchain_community",
    "langchain_openai",
    "langchain_anthropic",
    "langchain_google_genai",
    "langchain_chroma",
    "langgraph",
    "langsmith",
    "pydantic",
]

print("=== Package versions ===")
all_ok = all(check_import(name) for name in packages_to_check)

# Smoke tests: instantiate + basic call for each provider you use
if all_ok:
    print("\n=== Smoke tests ===")

    from langchain_core.prompts import ChatPromptTemplate
    from langchain_core.output_parsers import StrOutputParser
    from langchain_openai import ChatOpenAI
    from langchain_anthropic import ChatAnthropic

    prompt = ChatPromptTemplate.from_template("Say hi in one word.")

    for name, llm_factory in [
        ("openai",     lambda: ChatOpenAI(model="gpt-4o-mini")),
        ("anthropic",  lambda: ChatAnthropic(model="claude-haiku-4-5-20251001")),
    ]:
        try:
            chain = prompt | llm_factory() | StrOutputParser()
            result = chain.invoke({})
            print(f"✓ {name:15s} chain works — got {result[:30]!r}")
        except Exception as e:
            print(f"✗ {name:15s} FAILED — {type(e).__name__}: {e}")

# Verify Pydantic version is 2.x
import pydantic
if pydantic.VERSION.split(".")[0] != "2":
    print(f"\n✗ WARNING: Pydantic is {pydantic.VERSION}; LangChain 0.3+ requires v2")

# Notable LangChain migrations (as of 2026)

## 0.3 (October 2024)
Breaking: Pydantic v1 no longer supported anywhere
Breaking: `langchain.embeddings.OpenAIEmbeddings` moved to `langchain_openai.OpenAIEmbeddings`
Deprecated: Old memory classes (ConversationBufferMemory, etc.)
Deprecated: LLMChain, ConversationChain
Migration: See our "Deprecated memory migration" page (page 99)

## 0.2 (May 2024)
Breaking: Provider integrations split into separate packages
Breaking: `langchain.chat_models` no longer contains the actual implementations
  - `from langchain.chat_models import ChatOpenAI` STILL WORKS via shim
  - PREFERRED: `from langchain_openai import ChatOpenAI`
Breaking: `LangChainOutputParserException` renamed to `OutputParserException`

## 0.1 (January 2024)
Breaking: LangChain Expression Language (LCEL) becomes the primary API
Legacy: Chain classes still work but no longer the recommended pattern

## Ongoing (0.3.x minor releases)
- New AIMessage tool_calls / usage_metadata field standardisation
- with_structured_output method="json_schema" support expanded to more providers
- Provider-specific betas may add/rename beta headers

## Watch for
- LangGraph 0.x → 1.0 migration (upcoming; watch langgraph release notes)
- LangSmith SDK client rewrites (occasional; usually additive)
- Individual provider SDKs bumping major versions (langchain-openai stays in sync with openai SDK majors)

# Practical approach:
# 1) Subscribe to LangChain GitHub releases
# 2) Follow the LangChain blog for major version launches
# 3) Run version_audit.py after every upgrade