x

- retry_model_request hook lets a middleware decide to retry a failed
model request, with full ability to modify as much or as little of the
request before doing so
- ModelFallbackMiddleware tries each fallback model in order, until one
is successful, or fallback list is exhausted

Co-authored-by: Sydney Runkle <54324534+sydney-runkle@users.noreply.github.com>

.claude/settings.local.json

@@ -0,0 +1,15 @@
+{
+  "permissions": {
+    "allow": [
+      "Bash(uv run:*)",
+      "Bash(make:*)",
+      "WebSearch",
+      "WebFetch(domain:ai.pydantic.dev)",
+      "WebFetch(domain:openai.github.io)",
+      "Bash(uv run:*)",
+      "Bash(python3:*)"
+    ],
+    "deny": [],
+    "ask": []
+  }
+}

.github/scripts/check_diff.py

@@ -50,10 +50,6 @@ IGNORED_PARTNERS = [
     "prompty",
 ]
 
-PY_312_MAX_PACKAGES = [
-    "libs/partners/chroma",  # https://github.com/chroma-core/chroma/issues/4382
-]
-
 
 def all_package_dirs() -> Set[str]:
     return {
@@ -139,9 +135,6 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
         py_versions = ["3.10", "3.11", "3.12", "3.13"]
     # custom logic for specific directories
 
-    elif dir_ in PY_312_MAX_PACKAGES:
-        py_versions = ["3.10", "3.12"]
-
     elif dir_ == "libs/langchain" and job == "extended-tests":
         py_versions = ["3.10", "3.13"]
     elif dir_ == "libs/langchain_v1":
@@ -310,6 +303,11 @@ if __name__ == "__main__":
                 dirs_to_run["codspeed"].add(f"libs/partners/{partner_dir}")
             # Skip if the directory was deleted or is just a tombstone readme
         elif file.startswith("libs/"):
+            # Check if this is a root-level file in libs/ (e.g., libs/README.md)
+            file_parts = file.split("/")
+            if len(file_parts) == 2:
+                # Root-level file in libs/, skip it (no tests needed)
+                continue
             raise ValueError(
                 f"Unknown lib: {file}. check_diff.py likely needs "
                 "an update for this new library!"

.github/workflows/api_doc_build.yml

@@ -0,0 +1,152 @@
+# Build the API reference documentation for v0.3 branch.
+#
+# Manual trigger only.
+#
+# Built HTML pushed to langchain-ai/langchain-api-docs-html.
+#
+# Looks for langchain-ai org repos in packages.yml and checks them out.
+# Calls prep_api_docs_build.py.
+
+name: "📚 API Docs (v0.3)"
+run-name: "Build & Deploy API Reference (v0.3)"
+
+on:
+  workflow_dispatch:
+
+env:
+  PYTHON_VERSION: "3.11"
+
+jobs:
+  build:
+    if: github.repository == 'langchain-ai/langchain' || github.event_name != 'schedule'
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+    steps:
+      - uses: actions/checkout@v5
+        with:
+          ref: v0.3
+          path: langchain
+
+      - uses: actions/checkout@v5
+        with:
+          repository: langchain-ai/langchain-api-docs-html
+          path: langchain-api-docs-html
+          token: ${{ secrets.TOKEN_GITHUB_API_DOCS_HTML }}
+
+      - name: "📋 Extract Repository List with yq"
+        id: get-unsorted-repos
+        uses: mikefarah/yq@master
+        with:
+          cmd: |
+            # Extract repos from packages.yml that are in the langchain-ai org
+            # (excluding 'langchain' itself)
+            yq '
+              .packages[]
+              | select(
+                  (
+                    (.repo | test("^langchain-ai/"))
+                    and
+                    (.repo != "langchain-ai/langchain")
+                  )
+                  or
+                  (.include_in_api_ref // false)
+                )
+              | .repo
+            ' langchain/libs/packages.yml
+
+      - name: "📋 Parse YAML & Checkout Repositories"
+        env:
+          REPOS_UNSORTED: ${{ steps.get-unsorted-repos.outputs.result }}
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          # Get unique repositories
+          REPOS=$(echo "$REPOS_UNSORTED" | sort -u)
+          # Checkout each unique repository
+          for repo in $REPOS; do
+            # Validate repository format (allow any org with proper format)
+            if [[ ! "$repo" =~ ^[a-zA-Z0-9_.-]+/[a-zA-Z0-9_.-]+$ ]]; then
+              echo "Error: Invalid repository format: $repo"
+              exit 1
+            fi
+
+            REPO_NAME=$(echo $repo | cut -d'/' -f2)
+
+            # Additional validation for repo name
+            if [[ ! "$REPO_NAME" =~ ^[a-zA-Z0-9_.-]+$ ]]; then
+              echo "Error: Invalid repository name: $REPO_NAME"
+              exit 1
+            fi
+            echo "Checking out $repo to $REPO_NAME"
+            git clone --depth 1 https://github.com/$repo.git $REPO_NAME
+          done
+
+      - name: "🐍 Setup Python ${{ env.PYTHON_VERSION }}"
+        uses: actions/setup-python@v6
+        id: setup-python
+        with:
+          python-version: ${{ env.PYTHON_VERSION }}
+
+      - name: "📦 Install Initial Python Dependencies using uv"
+        working-directory: langchain
+        run: |
+          python -m pip install -U uv
+          python -m uv pip install --upgrade --no-cache-dir pip setuptools pyyaml
+
+      - name: "📦 Organize Library Directories"
+        # Places cloned partner packages into libs/partners structure
+        run: python langchain/.github/scripts/prep_api_docs_build.py
+
+      - name: "🧹 Clear Prior Build"
+        run:
+          # Remove artifacts from prior docs build
+          rm -rf langchain-api-docs-html/api_reference_build/html
+
+      - name: "📦 Install Documentation Dependencies using uv"
+        working-directory: langchain
+        run: |
+          # Install all partner packages in editable mode with overrides
+          python -m uv pip install $(ls ./libs/partners | xargs -I {} echo "./libs/partners/{}") --overrides ./docs/vercel_overrides.txt
+
+          # Install core langchain and other main packages
+          python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental libs/standard-tests
+
+          # Install Sphinx and related packages for building docs
+          python -m uv pip install -r docs/api_reference/requirements.txt
+
+      - name: "🔧 Configure Git Settings"
+        working-directory: langchain
+        run: |
+          git config --local user.email "actions@github.com"
+          git config --local user.name "Github Actions"
+
+      - name: "📚 Build API Documentation"
+        working-directory: langchain
+        run: |
+          # Generate the API reference RST files
+          python docs/api_reference/create_api_rst.py
+
+          # Build the HTML documentation using Sphinx
+          # -T: show full traceback on exception
+          # -E: don't use cached environment (force rebuild, ignore cached doctrees)
+          # -b html: build HTML docs (vs PDS, etc.)
+          # -d: path for the cached environment (parsed document trees / doctrees)
+          #     - Separate from output dir for faster incremental builds
+          # -c: path to conf.py
+          # -j auto: parallel build using all available CPU cores
+          python -m sphinx -T -E -b html -d ../langchain-api-docs-html/_build/doctrees -c docs/api_reference docs/api_reference ../langchain-api-docs-html/api_reference_build/html -j auto
+
+          # Post-process the generated HTML
+          python docs/api_reference/scripts/custom_formatter.py ../langchain-api-docs-html/api_reference_build/html
+
+          # Default index page is blank so we copy in the actual home page.
+          cp ../langchain-api-docs-html/api_reference_build/html/{reference,index}.html
+
+          # Removes Sphinx's intermediate build artifacts after the build is complete.
+          rm -rf ../langchain-api-docs-html/_build/
+
+      # Commit and push changes to langchain-api-docs-html repo
+      - uses: EndBug/add-and-commit@v9
+        with:
+          cwd: langchain-api-docs-html
+          message: "Update API docs build from v0.3 branch"

.pre-commit-config.yaml

@@ -97,9 +97,3 @@ repos:
         entry: make -C libs/partners/qdrant format lint
         files: ^libs/partners/qdrant/
         pass_filenames: false
-      - id: root
-        name: format and lint docs, cookbook
-        language: system
-        entry: make format lint
-        files: ^(docs|cookbook)/
-        pass_filenames: false

libs/README.md

@@ -0,0 +1,2 @@
+> [!IMPORTANT]
+> [**View all LangChain integrations packages**](https://docs.langchain.com/oss/python/integrations/providers)

libs/cli/langchain_cli/namespaces/migrate/.grit/patterns/langchain_to_core.json

@@ -1,5 +1,8 @@
 [
-  ["langchain._api.deprecated", "langchain_core._api.deprecated"],
+  [
+    "langchain._api.deprecated",
+    "langchain_core._api.deprecated"
+  ],
   [
     "langchain._api.LangChainDeprecationWarning",
     "langchain_core._api.LangChainDeprecationWarning"
@@ -12,7 +15,10 @@
     "langchain._api.surface_langchain_deprecation_warnings",
     "langchain_core._api.surface_langchain_deprecation_warnings"
   ],
-  ["langchain._api.warn_deprecated", "langchain_core._api.warn_deprecated"],
+  [
+    "langchain._api.warn_deprecated",
+    "langchain_core._api.warn_deprecated"
+  ],
   [
     "langchain._api.deprecation.LangChainDeprecationWarning",
     "langchain_core._api.LangChainDeprecationWarning"
@@ -21,7 +27,10 @@
     "langchain._api.deprecation.LangChainPendingDeprecationWarning",
     "langchain_core._api.deprecation.LangChainPendingDeprecationWarning"
   ],
-  ["langchain._api.deprecation.deprecated", "langchain_core._api.deprecated"],
+  [
+    "langchain._api.deprecation.deprecated",
+    "langchain_core._api.deprecated"
+  ],
   [
     "langchain._api.deprecation.suppress_langchain_deprecation_warning",
     "langchain_core._api.suppress_langchain_deprecation_warning"
@@ -38,12 +47,30 @@
     "langchain._api.path.get_relative_path",
     "langchain_core._api.get_relative_path"
   ],
-  ["langchain._api.path.as_import_path", "langchain_core._api.as_import_path"],
-  ["langchain.agents.Tool", "langchain_core.tools.Tool"],
-  ["langchain.agents.tool", "langchain_core.tools.tool"],
-  ["langchain.agents.tools.BaseTool", "langchain_core.tools.BaseTool"],
-  ["langchain.agents.tools.tool", "langchain_core.tools.tool"],
-  ["langchain.agents.tools.Tool", "langchain_core.tools.Tool"],
+  [
+    "langchain._api.path.as_import_path",
+    "langchain_core._api.as_import_path"
+  ],
+  [
+    "langchain.agents.Tool",
+    "langchain_core.tools.Tool"
+  ],
+  [
+    "langchain.agents.tool",
+    "langchain_core.tools.tool"
+  ],
+  [
+    "langchain.agents.tools.BaseTool",
+    "langchain_core.tools.BaseTool"
+  ],
+  [
+    "langchain.agents.tools.tool",
+    "langchain_core.tools.tool"
+  ],
+  [
+    "langchain.agents.tools.Tool",
+    "langchain_core.tools.Tool"
+  ],
   [
     "langchain.base_language.BaseLanguageModel",
     "langchain_core.language_models.BaseLanguageModel"
@@ -60,10 +87,6 @@
     "langchain.callbacks.LangChainTracer",
     "langchain_core.tracers.LangChainTracer"
   ],
-  [
-    "langchain.callbacks.tracing_enabled",
-    "langchain_core.tracers.context.tracing_enabled"
-  ],
   [
     "langchain.callbacks.tracing_v2_enabled",
     "langchain_core.tracers.context.tracing_v2_enabled"
@@ -300,7 +323,10 @@
     "langchain.callbacks.tracers.schemas.LLMRun",
     "langchain_core.tracers.schemas.LLMRun"
   ],
-  ["langchain.callbacks.tracers.schemas.Run", "langchain_core.tracers.Run"],
+  [
+    "langchain.callbacks.tracers.schemas.Run",
+    "langchain_core.tracers.Run"
+  ],
   [
     "langchain.callbacks.tracers.schemas.RunTypeEnum",
     "langchain_core.tracers.schemas.RunTypeEnum"
@@ -361,8 +387,14 @@
     "langchain.chat_models.base.agenerate_from_stream",
     "langchain_core.language_models.chat_models.agenerate_from_stream"
   ],
-  ["langchain.docstore.document.Document", "langchain_core.documents.Document"],
-  ["langchain.document_loaders.Blob", "langchain_core.document_loaders.Blob"],
+  [
+    "langchain.docstore.document.Document",
+    "langchain_core.documents.Document"
+  ],
+  [
+    "langchain.document_loaders.Blob",
+    "langchain_core.document_loaders.Blob"
+  ],
   [
     "langchain.document_loaders.BlobLoader",
     "langchain_core.document_loaders.BlobLoader"
@@ -399,29 +431,74 @@
     "langchain.formatting.StrictFormatter",
     "langchain_core.utils.StrictFormatter"
   ],
-  ["langchain.input.get_bolded_text", "langchain_core.utils.get_bolded_text"],
+  [
+    "langchain.input.get_bolded_text",
+    "langchain_core.utils.get_bolded_text"
+  ],
   [
     "langchain.input.get_color_mapping",
     "langchain_core.utils.get_color_mapping"
   ],
-  ["langchain.input.get_colored_text", "langchain_core.utils.get_colored_text"],
-  ["langchain.input.print_text", "langchain_core.utils.print_text"],
+  [
+    "langchain.input.get_colored_text",
+    "langchain_core.utils.get_colored_text"
+  ],
+  [
+    "langchain.input.print_text",
+    "langchain_core.utils.print_text"
+  ],
   [
     "langchain.llms.base.BaseLanguageModel",
     "langchain_core.language_models.BaseLanguageModel"
   ],
-  ["langchain.llms.base.BaseLLM", "langchain_core.language_models.BaseLLM"],
-  ["langchain.llms.base.LLM", "langchain_core.language_models.LLM"],
-  ["langchain.load.dumpd", "langchain_core.load.dumpd"],
-  ["langchain.load.dumps", "langchain_core.load.dumps"],
-  ["langchain.load.load", "langchain_core.load.load"],
-  ["langchain.load.loads", "langchain_core.load.loads"],
-  ["langchain.load.dump.default", "langchain_core.load.dump.default"],
-  ["langchain.load.dump.dumps", "langchain_core.load.dumps"],
-  ["langchain.load.dump.dumpd", "langchain_core.load.dumpd"],
-  ["langchain.load.load.Reviver", "langchain_core.load.load.Reviver"],
-  ["langchain.load.load.loads", "langchain_core.load.loads"],
-  ["langchain.load.load.load", "langchain_core.load.load"],
+  [
+    "langchain.llms.base.BaseLLM",
+    "langchain_core.language_models.BaseLLM"
+  ],
+  [
+    "langchain.llms.base.LLM",
+    "langchain_core.language_models.LLM"
+  ],
+  [
+    "langchain.load.dumpd",
+    "langchain_core.load.dumpd"
+  ],
+  [
+    "langchain.load.dumps",
+    "langchain_core.load.dumps"
+  ],
+  [
+    "langchain.load.load",
+    "langchain_core.load.load"
+  ],
+  [
+    "langchain.load.loads",
+    "langchain_core.load.loads"
+  ],
+  [
+    "langchain.load.dump.default",
+    "langchain_core.load.dump.default"
+  ],
+  [
+    "langchain.load.dump.dumps",
+    "langchain_core.load.dumps"
+  ],
+  [
+    "langchain.load.dump.dumpd",
+    "langchain_core.load.dumpd"
+  ],
+  [
+    "langchain.load.load.Reviver",
+    "langchain_core.load.load.Reviver"
+  ],
+  [
+    "langchain.load.load.loads",
+    "langchain_core.load.loads"
+  ],
+  [
+    "langchain.load.load.load",
+    "langchain_core.load.load"
+  ],
   [
     "langchain.load.serializable.BaseSerialized",
     "langchain_core.load.serializable.BaseSerialized"
@@ -602,7 +679,10 @@
     "langchain.prompts.PipelinePromptTemplate",
     "langchain_core.prompts.PipelinePromptTemplate"
   ],
-  ["langchain.prompts.PromptTemplate", "langchain_core.prompts.PromptTemplate"],
+  [
+    "langchain.prompts.PromptTemplate",
+    "langchain_core.prompts.PromptTemplate"
+  ],
   [
     "langchain.prompts.SemanticSimilarityExampleSelector",
     "langchain_core.example_selectors.SemanticSimilarityExampleSelector"
@@ -615,12 +695,18 @@
     "langchain.prompts.SystemMessagePromptTemplate",
     "langchain_core.prompts.SystemMessagePromptTemplate"
   ],
-  ["langchain.prompts.load_prompt", "langchain_core.prompts.load_prompt"],
+  [
+    "langchain.prompts.load_prompt",
+    "langchain_core.prompts.load_prompt"
+  ],
   [
     "langchain.prompts.FewShotChatMessagePromptTemplate",
     "langchain_core.prompts.FewShotChatMessagePromptTemplate"
   ],
-  ["langchain.prompts.Prompt", "langchain_core.prompts.PromptTemplate"],
+  [
+    "langchain.prompts.Prompt",
+    "langchain_core.prompts.PromptTemplate"
+  ],
   [
     "langchain.prompts.base.jinja2_formatter",
     "langchain_core.prompts.jinja2_formatter"
@@ -801,13 +887,34 @@
     "langchain.prompts.prompt.PromptTemplate",
     "langchain_core.prompts.PromptTemplate"
   ],
-  ["langchain.prompts.prompt.Prompt", "langchain_core.prompts.PromptTemplate"],
-  ["langchain.schema.BaseCache", "langchain_core.caches.BaseCache"],
-  ["langchain.schema.BaseMemory", "langchain_core.memory.BaseMemory"],
-  ["langchain.schema.BaseStore", "langchain_core.stores.BaseStore"],
-  ["langchain.schema.AgentFinish", "langchain_core.agents.AgentFinish"],
-  ["langchain.schema.AgentAction", "langchain_core.agents.AgentAction"],
-  ["langchain.schema.Document", "langchain_core.documents.Document"],
+  [
+    "langchain.prompts.prompt.Prompt",
+    "langchain_core.prompts.PromptTemplate"
+  ],
+  [
+    "langchain.schema.BaseCache",
+    "langchain_core.caches.BaseCache"
+  ],
+  [
+    "langchain.schema.BaseMemory",
+    "langchain_core.memory.BaseMemory"
+  ],
+  [
+    "langchain.schema.BaseStore",
+    "langchain_core.stores.BaseStore"
+  ],
+  [
+    "langchain.schema.AgentFinish",
+    "langchain_core.agents.AgentFinish"
+  ],
+  [
+    "langchain.schema.AgentAction",
+    "langchain_core.agents.AgentAction"
+  ],
+  [
+    "langchain.schema.Document",
+    "langchain_core.documents.Document"
+  ],
   [
     "langchain.schema.BaseChatMessageHistory",
     "langchain_core.chat_history.BaseChatMessageHistory"
@@ -816,15 +923,30 @@
     "langchain.schema.BaseDocumentTransformer",
     "langchain_core.documents.BaseDocumentTransformer"
   ],
-  ["langchain.schema.BaseMessage", "langchain_core.messages.BaseMessage"],
-  ["langchain.schema.ChatMessage", "langchain_core.messages.ChatMessage"],
+  [
+    "langchain.schema.BaseMessage",
+    "langchain_core.messages.BaseMessage"
+  ],
+  [
+    "langchain.schema.ChatMessage",
+    "langchain_core.messages.ChatMessage"
+  ],
   [
     "langchain.schema.FunctionMessage",
     "langchain_core.messages.FunctionMessage"
   ],
-  ["langchain.schema.HumanMessage", "langchain_core.messages.HumanMessage"],
-  ["langchain.schema.AIMessage", "langchain_core.messages.AIMessage"],
-  ["langchain.schema.SystemMessage", "langchain_core.messages.SystemMessage"],
+  [
+    "langchain.schema.HumanMessage",
+    "langchain_core.messages.HumanMessage"
+  ],
+  [
+    "langchain.schema.AIMessage",
+    "langchain_core.messages.AIMessage"
+  ],
+  [
+    "langchain.schema.SystemMessage",
+    "langchain_core.messages.SystemMessage"
+  ],
   [
     "langchain.schema.messages_from_dict",
     "langchain_core.messages.messages_from_dict"
@@ -849,18 +971,42 @@
     "langchain.schema.get_buffer_string",
     "langchain_core.messages.get_buffer_string"
   ],
-  ["langchain.schema.RunInfo", "langchain_core.outputs.RunInfo"],
-  ["langchain.schema.LLMResult", "langchain_core.outputs.LLMResult"],
-  ["langchain.schema.ChatResult", "langchain_core.outputs.ChatResult"],
-  ["langchain.schema.ChatGeneration", "langchain_core.outputs.ChatGeneration"],
-  ["langchain.schema.Generation", "langchain_core.outputs.Generation"],
-  ["langchain.schema.PromptValue", "langchain_core.prompt_values.PromptValue"],
+  [
+    "langchain.schema.RunInfo",
+    "langchain_core.outputs.RunInfo"
+  ],
+  [
+    "langchain.schema.LLMResult",
+    "langchain_core.outputs.LLMResult"
+  ],
+  [
+    "langchain.schema.ChatResult",
+    "langchain_core.outputs.ChatResult"
+  ],
+  [
+    "langchain.schema.ChatGeneration",
+    "langchain_core.outputs.ChatGeneration"
+  ],
+  [
+    "langchain.schema.Generation",
+    "langchain_core.outputs.Generation"
+  ],
+  [
+    "langchain.schema.PromptValue",
+    "langchain_core.prompt_values.PromptValue"
+  ],
   [
     "langchain.schema.LangChainException",
     "langchain_core.exceptions.LangChainException"
   ],
-  ["langchain.schema.BaseRetriever", "langchain_core.retrievers.BaseRetriever"],
-  ["langchain.schema.Memory", "langchain_core.memory.BaseMemory"],
+  [
+    "langchain.schema.BaseRetriever",
+    "langchain_core.retrievers.BaseRetriever"
+  ],
+  [
+    "langchain.schema.Memory",
+    "langchain_core.memory.BaseMemory"
+  ],
   [
     "langchain.schema.OutputParserException",
     "langchain_core.exceptions.OutputParserException"
@@ -885,13 +1031,22 @@
     "langchain.schema.format_document",
     "langchain_core.prompts.format_document"
   ],
-  ["langchain.schema.agent.AgentAction", "langchain_core.agents.AgentAction"],
+  [
+    "langchain.schema.agent.AgentAction",
+    "langchain_core.agents.AgentAction"
+  ],
   [
     "langchain.schema.agent.AgentActionMessageLog",
     "langchain_core.agents.AgentActionMessageLog"
   ],
-  ["langchain.schema.agent.AgentFinish", "langchain_core.agents.AgentFinish"],
-  ["langchain.schema.cache.BaseCache", "langchain_core.caches.BaseCache"],
+  [
+    "langchain.schema.agent.AgentFinish",
+    "langchain_core.agents.AgentFinish"
+  ],
+  [
+    "langchain.schema.cache.BaseCache",
+    "langchain_core.caches.BaseCache"
+  ],
   [
     "langchain.schema.callbacks.base.RetrieverManagerMixin",
     "langchain_core.callbacks.RetrieverManagerMixin"
@@ -1168,7 +1323,10 @@
     "langchain.schema.chat_history.BaseChatMessageHistory",
     "langchain_core.chat_history.BaseChatMessageHistory"
   ],
-  ["langchain.schema.document.Document", "langchain_core.documents.Document"],
+  [
+    "langchain.schema.document.Document",
+    "langchain_core.documents.Document"
+  ],
   [
     "langchain.schema.document.BaseDocumentTransformer",
     "langchain_core.documents.BaseDocumentTransformer"
@@ -1189,7 +1347,10 @@
     "langchain.schema.language_model._get_token_ids_default_method",
     "langchain_core.language_models.base._get_token_ids_default_method"
   ],
-  ["langchain.schema.memory.BaseMemory", "langchain_core.memory.BaseMemory"],
+  [
+    "langchain.schema.memory.BaseMemory",
+    "langchain_core.memory.BaseMemory"
+  ],
   [
     "langchain.schema.messages.get_buffer_string",
     "langchain_core.messages.get_buffer_string"
@@ -1214,7 +1375,10 @@
     "langchain.schema.messages.HumanMessageChunk",
     "langchain_core.messages.HumanMessageChunk"
   ],
-  ["langchain.schema.messages.AIMessage", "langchain_core.messages.AIMessage"],
+  [
+    "langchain.schema.messages.AIMessage",
+    "langchain_core.messages.AIMessage"
+  ],
   [
     "langchain.schema.messages.AIMessageChunk",
     "langchain_core.messages.AIMessageChunk"
@@ -1271,7 +1435,10 @@
     "langchain.schema.messages.message_to_dict",
     "langchain_core.messages.message_to_dict"
   ],
-  ["langchain.schema.output.Generation", "langchain_core.outputs.Generation"],
+  [
+    "langchain.schema.output.Generation",
+    "langchain_core.outputs.Generation"
+  ],
   [
     "langchain.schema.output.GenerationChunk",
     "langchain_core.outputs.GenerationChunk"
@@ -1284,9 +1451,18 @@
     "langchain.schema.output.ChatGenerationChunk",
     "langchain_core.outputs.ChatGenerationChunk"
   ],
-  ["langchain.schema.output.RunInfo", "langchain_core.outputs.RunInfo"],
-  ["langchain.schema.output.ChatResult", "langchain_core.outputs.ChatResult"],
-  ["langchain.schema.output.LLMResult", "langchain_core.outputs.LLMResult"],
+  [
+    "langchain.schema.output.RunInfo",
+    "langchain_core.outputs.RunInfo"
+  ],
+  [
+    "langchain.schema.output.ChatResult",
+    "langchain_core.outputs.ChatResult"
+  ],
+  [
+    "langchain.schema.output.LLMResult",
+    "langchain_core.outputs.LLMResult"
+  ],
   [
     "langchain.schema.output_parser.BaseLLMOutputParser",
     "langchain_core.output_parsers.BaseLLMOutputParser"
@@ -1359,7 +1535,10 @@
     "langchain.schema.runnable.RouterRunnable",
     "langchain_core.runnables.RouterRunnable"
   ],
-  ["langchain.schema.runnable.Runnable", "langchain_core.runnables.Runnable"],
+  [
+    "langchain.schema.runnable.Runnable",
+    "langchain_core.runnables.Runnable"
+  ],
   [
     "langchain.schema.runnable.RunnableSerializable",
     "langchain_core.runnables.RunnableSerializable"
@@ -1596,7 +1775,10 @@
     "langchain.schema.runnable.utils.SupportsAdd",
     "langchain_core.runnables.utils.SupportsAdd"
   ],
-  ["langchain.schema.runnable.utils.add", "langchain_core.runnables.add"],
+  [
+    "langchain.schema.runnable.utils.add",
+    "langchain_core.runnables.add"
+  ],
   [
     "langchain.schema.runnable.utils.ConfigurableField",
     "langchain_core.runnables.ConfigurableField"
@@ -1617,7 +1799,10 @@
     "langchain.schema.runnable.utils.get_unique_config_specs",
     "langchain_core.runnables.utils.get_unique_config_specs"
   ],
-  ["langchain.schema.runnable.utils.aadd", "langchain_core.runnables.aadd"],
+  [
+    "langchain.schema.runnable.utils.aadd",
+    "langchain_core.runnables.aadd"
+  ],
   [
     "langchain.schema.runnable.utils.gated_coro",
     "langchain_core.runnables.utils.gated_coro"
@@ -1626,7 +1811,10 @@
     "langchain.schema.runnable.utils.gather_with_concurrency",
     "langchain_core.runnables.utils.gather_with_concurrency"
   ],
-  ["langchain.schema.storage.BaseStore", "langchain_core.stores.BaseStore"],
+  [
+    "langchain.schema.storage.BaseStore",
+    "langchain_core.stores.BaseStore"
+  ],
   [
     "langchain.schema.vectorstore.VectorStore",
     "langchain_core.vectorstores.VectorStore"
@@ -1635,14 +1823,26 @@
     "langchain.schema.vectorstore.VectorStoreRetriever",
     "langchain_core.vectorstores.VectorStoreRetriever"
   ],
-  ["langchain.tools.BaseTool", "langchain_core.tools.BaseTool"],
-  ["langchain.tools.StructuredTool", "langchain_core.tools.StructuredTool"],
-  ["langchain.tools.Tool", "langchain_core.tools.Tool"],
+  [
+    "langchain.tools.BaseTool",
+    "langchain_core.tools.BaseTool"
+  ],
+  [
+    "langchain.tools.StructuredTool",
+    "langchain_core.tools.StructuredTool"
+  ],
+  [
+    "langchain.tools.Tool",
+    "langchain_core.tools.Tool"
+  ],
   [
     "langchain.tools.format_tool_to_openai_function",
     "langchain_core.utils.function_calling.format_tool_to_openai_function"
   ],
-  ["langchain.tools.tool", "langchain_core.tools.tool"],
+  [
+    "langchain.tools.tool",
+    "langchain_core.tools.tool"
+  ],
   [
     "langchain.tools.base.SchemaAnnotationError",
     "langchain_core.tools.SchemaAnnotationError"
@@ -1651,14 +1851,26 @@
     "langchain.tools.base.create_schema_from_function",
     "langchain_core.tools.create_schema_from_function"
   ],
-  ["langchain.tools.base.ToolException", "langchain_core.tools.ToolException"],
-  ["langchain.tools.base.BaseTool", "langchain_core.tools.BaseTool"],
-  ["langchain.tools.base.Tool", "langchain_core.tools.Tool"],
+  [
+    "langchain.tools.base.ToolException",
+    "langchain_core.tools.ToolException"
+  ],
+  [
+    "langchain.tools.base.BaseTool",
+    "langchain_core.tools.BaseTool"
+  ],
+  [
+    "langchain.tools.base.Tool",
+    "langchain_core.tools.Tool"
+  ],
   [
     "langchain.tools.base.StructuredTool",
     "langchain_core.tools.StructuredTool"
   ],
-  ["langchain.tools.base.tool", "langchain_core.tools.tool"],
+  [
+    "langchain.tools.base.tool",
+    "langchain_core.tools.tool"
+  ],
   [
     "langchain.tools.convert_to_openai.format_tool_to_openai_function",
     "langchain_core.utils.function_calling.format_tool_to_openai_function"
@@ -1675,49 +1887,94 @@
     "langchain.utilities.loading.try_load_from_hub",
     "langchain_core.utils.try_load_from_hub"
   ],
-  ["langchain.utils.StrictFormatter", "langchain_core.utils.StrictFormatter"],
+  [
+    "langchain.utils.StrictFormatter",
+    "langchain_core.utils.StrictFormatter"
+  ],
   [
     "langchain.utils.check_package_version",
     "langchain_core.utils.check_package_version"
   ],
-  ["langchain.utils.comma_list", "langchain_core.utils.comma_list"],
+  [
+    "langchain.utils.comma_list",
+    "langchain_core.utils.comma_list"
+  ],
   [
     "langchain.utils.convert_to_secret_str",
     "langchain_core.utils.convert_to_secret_str"
   ],
-  ["langchain.utils.get_bolded_text", "langchain_core.utils.get_bolded_text"],
+  [
+    "langchain.utils.get_bolded_text",
+    "langchain_core.utils.get_bolded_text"
+  ],
   [
     "langchain.utils.get_color_mapping",
     "langchain_core.utils.get_color_mapping"
   ],
-  ["langchain.utils.get_colored_text", "langchain_core.utils.get_colored_text"],
+  [
+    "langchain.utils.get_colored_text",
+    "langchain_core.utils.get_colored_text"
+  ],
   [
     "langchain.utils.get_from_dict_or_env",
     "langchain_core.utils.get_from_dict_or_env"
   ],
-  ["langchain.utils.get_from_env", "langchain_core.utils.get_from_env"],
+  [
+    "langchain.utils.get_from_env",
+    "langchain_core.utils.get_from_env"
+  ],
   [
     "langchain.utils.get_pydantic_field_names",
     "langchain_core.utils.get_pydantic_field_names"
   ],
-  ["langchain.utils.guard_import", "langchain_core.utils.guard_import"],
-  ["langchain.utils.mock_now", "langchain_core.utils.mock_now"],
-  ["langchain.utils.print_text", "langchain_core.utils.print_text"],
+  [
+    "langchain.utils.guard_import",
+    "langchain_core.utils.guard_import"
+  ],
+  [
+    "langchain.utils.mock_now",
+    "langchain_core.utils.mock_now"
+  ],
+  [
+    "langchain.utils.print_text",
+    "langchain_core.utils.print_text"
+  ],
   [
     "langchain.utils.raise_for_status_with_text",
     "langchain_core.utils.raise_for_status_with_text"
   ],
-  ["langchain.utils.stringify_dict", "langchain_core.utils.stringify_dict"],
-  ["langchain.utils.stringify_value", "langchain_core.utils.stringify_value"],
-  ["langchain.utils.xor_args", "langchain_core.utils.xor_args"],
-  ["langchain.utils.aiter.py_anext", "langchain_core.utils.aiter.py_anext"],
-  ["langchain.utils.aiter.NoLock", "langchain_core.utils.aiter.NoLock"],
-  ["langchain.utils.aiter.Tee", "langchain_core.utils.aiter.Tee"],
+  [
+    "langchain.utils.stringify_dict",
+    "langchain_core.utils.stringify_dict"
+  ],
+  [
+    "langchain.utils.stringify_value",
+    "langchain_core.utils.stringify_value"
+  ],
+  [
+    "langchain.utils.xor_args",
+    "langchain_core.utils.xor_args"
+  ],
+  [
+    "langchain.utils.aiter.py_anext",
+    "langchain_core.utils.aiter.py_anext"
+  ],
+  [
+    "langchain.utils.aiter.NoLock",
+    "langchain_core.utils.aiter.NoLock"
+  ],
+  [
+    "langchain.utils.aiter.Tee",
+    "langchain_core.utils.aiter.Tee"
+  ],
   [
     "langchain.utils.env.get_from_dict_or_env",
     "langchain_core.utils.get_from_dict_or_env"
   ],
-  ["langchain.utils.env.get_from_env", "langchain_core.utils.get_from_env"],
+  [
+    "langchain.utils.env.get_from_env",
+    "langchain_core.utils.get_from_env"
+  ],
   [
     "langchain.utils.formatting.StrictFormatter",
     "langchain_core.utils.StrictFormatter"
@@ -1742,10 +1999,22 @@
     "langchain.utils.input.get_bolded_text",
     "langchain_core.utils.get_bolded_text"
   ],
-  ["langchain.utils.input.print_text", "langchain_core.utils.print_text"],
-  ["langchain.utils.iter.NoLock", "langchain_core.utils.iter.NoLock"],
-  ["langchain.utils.iter.tee_peer", "langchain_core.utils.iter.tee_peer"],
-  ["langchain.utils.iter.Tee", "langchain_core.utils.iter.Tee"],
+  [
+    "langchain.utils.input.print_text",
+    "langchain_core.utils.print_text"
+  ],
+  [
+    "langchain.utils.iter.NoLock",
+    "langchain_core.utils.iter.NoLock"
+  ],
+  [
+    "langchain.utils.iter.tee_peer",
+    "langchain_core.utils.iter.tee_peer"
+  ],
+  [
+    "langchain.utils.iter.Tee",
+    "langchain_core.utils.iter.Tee"
+  ],
   [
     "langchain.utils.iter.batch_iterate",
     "langchain_core.utils.iter.batch_iterate"
@@ -1798,14 +2067,26 @@
     "langchain.utils.strings.stringify_dict",
     "langchain_core.utils.stringify_dict"
   ],
-  ["langchain.utils.strings.comma_list", "langchain_core.utils.comma_list"],
-  ["langchain.utils.utils.xor_args", "langchain_core.utils.xor_args"],
+  [
+    "langchain.utils.strings.comma_list",
+    "langchain_core.utils.comma_list"
+  ],
+  [
+    "langchain.utils.utils.xor_args",
+    "langchain_core.utils.xor_args"
+  ],
   [
     "langchain.utils.utils.raise_for_status_with_text",
     "langchain_core.utils.raise_for_status_with_text"
   ],
-  ["langchain.utils.utils.mock_now", "langchain_core.utils.mock_now"],
-  ["langchain.utils.utils.guard_import", "langchain_core.utils.guard_import"],
+  [
+    "langchain.utils.utils.mock_now",
+    "langchain_core.utils.mock_now"
+  ],
+  [
+    "langchain.utils.utils.guard_import",
+    "langchain_core.utils.guard_import"
+  ],
   [
     "langchain.utils.utils.check_package_version",
     "langchain_core.utils.check_package_version"

libs/core/langchain_core/chat_history.py

@@ -17,14 +17,12 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Union
+from typing import TYPE_CHECKING
 
 from pydantic import BaseModel, Field
 
 from langchain_core.messages import (
-    AIMessage,
     BaseMessage,
-    HumanMessage,
     get_buffer_string,
 )
 from langchain_core.runnables.config import run_in_executor
@@ -126,40 +124,6 @@ class BaseChatMessageHistory(ABC):
         """
         return await run_in_executor(None, lambda: self.messages)
 
-    def add_user_message(self, message: Union[HumanMessage, str]) -> None:
-        """Convenience method for adding a human message string to the store.
-
-        !!! note
-            This is a convenience method. Code should favor the bulk ``add_messages``
-            interface instead to save on round-trips to the persistence layer.
-
-        This method may be deprecated in a future release.
-
-        Args:
-            message: The human message to add to the store.
-        """
-        if isinstance(message, HumanMessage):
-            self.add_message(message)
-        else:
-            self.add_message(HumanMessage(content=message))
-
-    def add_ai_message(self, message: Union[AIMessage, str]) -> None:
-        """Convenience method for adding an AI message string to the store.
-
-        !!! note
-            This is a convenience method. Code should favor the bulk ``add_messages``
-            interface instead to save on round-trips to the persistence layer.
-
-        This method may be deprecated in a future release.
-
-        Args:
-            message: The AI message to add.
-        """
-        if isinstance(message, AIMessage):
-            self.add_message(message)
-        else:
-            self.add_message(AIMessage(content=message))
-
     def add_message(self, message: BaseMessage) -> None:
         """Add a Message object to the store.
 

libs/core/langchain_core/globals.py

@@ -1,18 +1,10 @@
 """Global values and configuration that apply to all of LangChain."""
 
-import warnings
 from typing import TYPE_CHECKING, Optional
 
 if TYPE_CHECKING:
     from langchain_core.caches import BaseCache
 
-try:
-    import langchain  # type: ignore[import-not-found]
-
-    _HAS_LANGCHAIN = True
-except ImportError:
-    _HAS_LANGCHAIN = False
-
 
 # DO NOT USE THESE VALUES DIRECTLY!
 # Use them only via `get_<X>()` and `set_<X>()` below,
@@ -29,26 +21,6 @@ def set_verbose(value: bool) -> None:  # noqa: FBT001
     Args:
         value: The new value for the `verbose` global setting.
     """
-    if _HAS_LANGCHAIN:
-        # We're about to run some deprecated code, don't report warnings from it.
-        # The user called the correct (non-deprecated) code path and shouldn't get
-        # warnings.
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                "ignore",
-                message=(
-                    "Importing verbose from langchain root module "
-                    "is no longer supported"
-                ),
-            )
-            # N.B.: This is a workaround for an unfortunate quirk of Python's
-            #       module-level `__getattr__()` implementation:
-            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-            #
-            # Remove it once `langchain.verbose` is no longer supported, and once all
-            # users have migrated to using `set_verbose()` here.
-            langchain.verbose = value
-
     global _verbose  # noqa: PLW0603
     _verbose = value
 
@@ -59,35 +31,7 @@ def get_verbose() -> bool:
     Returns:
         The value of the `verbose` global setting.
     """
-    if _HAS_LANGCHAIN:
-        # We're about to run some deprecated code, don't report warnings from it.
-        # The user called the correct (non-deprecated) code path and shouldn't get
-        # warnings.
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                "ignore",
-                message=(
-                    ".*Importing verbose from langchain root module "
-                    "is no longer supported"
-                ),
-            )
-            # N.B.: This is a workaround for an unfortunate quirk of Python's
-            #       module-level `__getattr__()` implementation:
-            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-            #
-            # Remove it once `langchain.verbose` is no longer supported, and once all
-            # users have migrated to using `set_verbose()` here.
-            #
-            # In the meantime, the `verbose` setting is considered True if either the
-            # old or the new value are True. This accommodates users who haven't
-            # migrated to using `set_verbose()` yet. Those users are getting
-            # deprecation warnings directing them to use `set_verbose()` when they
-            # import `langchain.verbose`.
-            old_verbose = langchain.verbose
-    else:
-        old_verbose = False
-
-    return _verbose or old_verbose
+    return _verbose
 
 
 def set_debug(value: bool) -> None:  # noqa: FBT001
@@ -96,24 +40,6 @@ def set_debug(value: bool) -> None:  # noqa: FBT001
     Args:
         value: The new value for the `debug` global setting.
     """
-    if _HAS_LANGCHAIN:
-        # We're about to run some deprecated code, don't report warnings from it.
-        # The user called the correct (non-deprecated) code path and shouldn't get
-        # warnings.
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                "ignore",
-                message="Importing debug from langchain root module "
-                "is no longer supported",
-            )
-            # N.B.: This is a workaround for an unfortunate quirk of Python's
-            #       module-level `__getattr__()` implementation:
-            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-            #
-            # Remove it once `langchain.debug` is no longer supported, and once all
-            # users have migrated to using `set_debug()` here.
-            langchain.debug = value
-
     global _debug  # noqa: PLW0603
     _debug = value
 
@@ -124,32 +50,7 @@ def get_debug() -> bool:
     Returns:
         The value of the `debug` global setting.
     """
-    if _HAS_LANGCHAIN:
-        # We're about to run some deprecated code, don't report warnings from it.
-        # The user called the correct (non-deprecated) code path and shouldn't get
-        # warnings.
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                "ignore",
-                message="Importing debug from langchain root module "
-                "is no longer supported",
-            )
-            # N.B.: This is a workaround for an unfortunate quirk of Python's
-            #       module-level `__getattr__()` implementation:
-            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-            #
-            # Remove it once `langchain.debug` is no longer supported, and once all
-            # users have migrated to using `set_debug()` here.
-            #
-            # In the meantime, the `debug` setting is considered True if either the old
-            # or the new value are True. This accommodates users who haven't migrated
-            # to using `set_debug()` yet. Those users are getting deprecation warnings
-            # directing them to use `set_debug()` when they import `langchain.debug`.
-            old_debug = langchain.debug
-    else:
-        old_debug = False
-
-    return _debug or old_debug
+    return _debug
 
 
 def set_llm_cache(value: Optional["BaseCache"]) -> None:
@@ -158,26 +59,6 @@ def set_llm_cache(value: Optional["BaseCache"]) -> None:
     Args:
         value: The new LLM cache to use. If `None`, the LLM cache is disabled.
     """
-    if _HAS_LANGCHAIN:
-        # We're about to run some deprecated code, don't report warnings from it.
-        # The user called the correct (non-deprecated) code path and shouldn't get
-        # warnings.
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                "ignore",
-                message=(
-                    "Importing llm_cache from langchain root module "
-                    "is no longer supported"
-                ),
-            )
-            # N.B.: This is a workaround for an unfortunate quirk of Python's
-            #       module-level `__getattr__()` implementation:
-            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-            #
-            # Remove it once `langchain.llm_cache` is no longer supported, and
-            # once all users have migrated to using `set_llm_cache()` here.
-            langchain.llm_cache = value
-
     global _llm_cache  # noqa: PLW0603
     _llm_cache = value
 
@@ -188,33 +69,4 @@ def get_llm_cache() -> Optional["BaseCache"]:
     Returns:
         The value of the `llm_cache` global setting.
     """
-    if _HAS_LANGCHAIN:
-        # We're about to run some deprecated code, don't report warnings from it.
-        # The user called the correct (non-deprecated) code path and shouldn't get
-        # warnings.
-        with warnings.catch_warnings():
-            warnings.filterwarnings(
-                "ignore",
-                message=(
-                    "Importing llm_cache from langchain root module "
-                    "is no longer supported"
-                ),
-            )
-            # N.B.: This is a workaround for an unfortunate quirk of Python's
-            #       module-level `__getattr__()` implementation:
-            # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-            #
-            # Remove it once `langchain.llm_cache` is no longer supported, and
-            # once all users have migrated to using `set_llm_cache()` here.
-            #
-            # In the meantime, the `llm_cache` setting returns whichever of
-            # its two backing sources is truthy (not `None` and non-empty),
-            # or the old value if both are falsy. This accommodates users
-            # who haven't migrated to using `set_llm_cache()` yet.
-            # Those users are getting deprecation warnings directing them
-            # to use `set_llm_cache()` when they import `langchain.llm_cache`.
-            old_llm_cache = langchain.llm_cache
-    else:
-        old_llm_cache = None
-
-    return _llm_cache or old_llm_cache
+    return _llm_cache

libs/core/langchain_core/language_models/base.py

@@ -20,7 +20,6 @@ from typing import (
 from pydantic import BaseModel, ConfigDict, Field, field_validator
 from typing_extensions import TypedDict, override
 
-from langchain_core._api import deprecated
 from langchain_core.caches import BaseCache
 from langchain_core.callbacks import Callbacks
 from langchain_core.globals import get_verbose
@@ -37,7 +36,6 @@ from langchain_core.prompt_values import (
     StringPromptValue,
 )
 from langchain_core.runnables import Runnable, RunnableSerializable
-from langchain_core.utils import get_pydantic_field_names
 
 if TYPE_CHECKING:
     from langchain_core.outputs import LLMResult
@@ -259,102 +257,6 @@ class BaseLanguageModel(
         # generate responses that match a given schema.
         raise NotImplementedError
 
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    @abstractmethod
-    def predict(
-        self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
-    ) -> str:
-        """Pass a single string input to the model and return a string.
-
-        Use this method when passing in raw text. If you want to pass in specific types
-        of chat messages, use predict_messages.
-
-        Args:
-            text: String input to pass to the model.
-            stop: Stop words to use when generating. Model output is cut off at the
-                first occurrence of any of these substrings.
-            **kwargs: Arbitrary additional keyword arguments. These are usually passed
-                to the model provider API call.
-
-        Returns:
-            Top model prediction as a string.
-
-        """
-
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    @abstractmethod
-    def predict_messages(
-        self,
-        messages: list[BaseMessage],
-        *,
-        stop: Optional[Sequence[str]] = None,
-        **kwargs: Any,
-    ) -> BaseMessage:
-        """Pass a message sequence to the model and return a message.
-
-        Use this method when passing in chat messages. If you want to pass in raw text,
-        use predict.
-
-        Args:
-            messages: A sequence of chat messages corresponding to a single model input.
-            stop: Stop words to use when generating. Model output is cut off at the
-                first occurrence of any of these substrings.
-            **kwargs: Arbitrary additional keyword arguments. These are usually passed
-                to the model provider API call.
-
-        Returns:
-            Top model prediction as a message.
-
-        """
-
-    @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
-    @abstractmethod
-    async def apredict(
-        self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
-    ) -> str:
-        """Asynchronously pass a string to the model and return a string.
-
-        Use this method when calling pure text generation models and only the top
-        candidate generation is needed.
-
-        Args:
-            text: String input to pass to the model.
-            stop: Stop words to use when generating. Model output is cut off at the
-                first occurrence of any of these substrings.
-            **kwargs: Arbitrary additional keyword arguments. These are usually passed
-                to the model provider API call.
-
-        Returns:
-            Top model prediction as a string.
-
-        """
-
-    @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
-    @abstractmethod
-    async def apredict_messages(
-        self,
-        messages: list[BaseMessage],
-        *,
-        stop: Optional[Sequence[str]] = None,
-        **kwargs: Any,
-    ) -> BaseMessage:
-        """Asynchronously pass messages to the model and return a message.
-
-        Use this method when calling chat models and only the top candidate generation
-        is needed.
-
-        Args:
-            messages: A sequence of chat messages corresponding to a single model input.
-            stop: Stop words to use when generating. Model output is cut off at the
-                first occurrence of any of these substrings.
-            **kwargs: Arbitrary additional keyword arguments. These are usually passed
-                to the model provider API call.
-
-        Returns:
-            Top model prediction as a message.
-
-        """
-
     @property
     def _identifying_params(self) -> Mapping[str, Any]:
         """Get the identifying parameters."""
@@ -417,12 +319,3 @@ class BaseLanguageModel(
                 stacklevel=2,
             )
         return sum(self.get_num_tokens(get_buffer_string([m])) for m in messages)
-
-    @classmethod
-    def _all_required_field_names(cls) -> set:
-        """DEPRECATED: Kept for backwards compatibility.
-
-        Use ``get_pydantic_field_names``.
-
-        """
-        return get_pydantic_field_names(cls)

libs/core/langchain_core/language_models/chat_models.py

@@ -6,22 +6,19 @@ import asyncio
 import inspect
 import json
 import typing
-import warnings
 from abc import ABC, abstractmethod
 from collections.abc import AsyncIterator, Iterator, Sequence
 from functools import cached_property
 from operator import itemgetter
 from typing import TYPE_CHECKING, Any, Callable, Literal, Optional, Union, cast
 
-from pydantic import BaseModel, ConfigDict, Field, model_validator
+from pydantic import BaseModel, ConfigDict, Field
 from typing_extensions import override
 
-from langchain_core._api import deprecated
 from langchain_core.caches import BaseCache
 from langchain_core.callbacks import (
     AsyncCallbackManager,
     AsyncCallbackManagerForLLMRun,
-    BaseCallbackManager,
     CallbackManager,
     CallbackManagerForLLMRun,
     Callbacks,
@@ -42,7 +39,6 @@ from langchain_core.messages import (
     AIMessageChunk,
     AnyMessage,
     BaseMessage,
-    HumanMessage,
     convert_to_messages,
     is_data_content_block,
     message_chunk_to_message,
@@ -319,16 +315,6 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
 
     """  # noqa: E501
 
-    callback_manager: Optional[BaseCallbackManager] = deprecated(
-        name="callback_manager", since="0.1.7", removal="1.0", alternative="callbacks"
-    )(
-        Field(
-            default=None,
-            exclude=True,
-            description="Callback manager to add to the run trace.",
-        )
-    )
-
     rate_limiter: Optional[BaseRateLimiter] = Field(default=None, exclude=True)
     "An optional rate limiter to use for limiting the number of requests."
 
@@ -373,27 +359,6 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
 
     """
 
-    @model_validator(mode="before")
-    @classmethod
-    def raise_deprecation(cls, values: dict) -> Any:
-        """Emit deprecation warning if ``callback_manager`` is used.
-
-        Args:
-            values (Dict): Values to validate.
-
-        Returns:
-            Dict: Validated values.
-
-        """
-        if values.get("callback_manager") is not None:
-            warnings.warn(
-                "callback_manager is deprecated. Please use callbacks instead.",
-                DeprecationWarning,
-                stacklevel=5,
-            )
-            values["callbacks"] = values.pop("callback_manager", None)
-        return values
-
     model_config = ConfigDict(
         arbitrary_types_allowed=True,
     )
@@ -1455,40 +1420,6 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
                 break
             yield item  # type: ignore[misc]
 
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    def __call__(
-        self,
-        messages: list[BaseMessage],
-        stop: Optional[list[str]] = None,
-        callbacks: Callbacks = None,
-        **kwargs: Any,
-    ) -> BaseMessage:
-        """Call the model.
-
-        Args:
-            messages: List of messages.
-            stop: Stop words to use when generating. Model output is cut off at the
-                first occurrence of any of these substrings.
-            callbacks: Callbacks to pass through. Used for executing additional
-                functionality, such as logging or streaming, throughout generation.
-            **kwargs: Arbitrary additional keyword arguments. These are usually passed
-                to the model provider API call.
-
-        Raises:
-            ValueError: If the generation is not a chat generation.
-
-        Returns:
-            The model output message.
-
-        """
-        generation = self.generate(
-            [messages], stop=stop, callbacks=callbacks, **kwargs
-        ).generations[0][0]
-        if isinstance(generation, ChatGeneration):
-            return generation.message
-        msg = "Unexpected generation type"
-        raise ValueError(msg)
-
     async def _call_async(
         self,
         messages: list[BaseMessage],
@@ -1505,91 +1436,6 @@ class BaseChatModel(BaseLanguageModel[AIMessage], ABC):
         msg = "Unexpected generation type"
         raise ValueError(msg)
 
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    def call_as_llm(
-        self, message: str, stop: Optional[list[str]] = None, **kwargs: Any
-    ) -> str:
-        """Call the model.
-
-        Args:
-            message: The input message.
-            stop: Stop words to use when generating. Model output is cut off at the
-                first occurrence of any of these substrings.
-            **kwargs: Arbitrary additional keyword arguments. These are usually passed
-                to the model provider API call.
-
-        Returns:
-            The model output string.
-
-        """
-        return self.predict(message, stop=stop, **kwargs)
-
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    @override
-    def predict(
-        self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
-    ) -> str:
-        """Predict the next message.
-
-        Args:
-            text: The input message.
-            stop: Stop words to use when generating. Model output is cut off at the
-                first occurrence of any of these substrings.
-            **kwargs: Arbitrary additional keyword arguments. These are usually passed
-                to the model provider API call.
-
-        Raises:
-            ValueError: If the output is not a string.
-
-        Returns:
-            The predicted output string.
-
-        """
-        stop_ = None if stop is None else list(stop)
-        result = self([HumanMessage(content=text)], stop=stop_, **kwargs)
-        if isinstance(result.content, str):
-            return result.content
-        msg = "Cannot use predict when output is not a string."
-        raise ValueError(msg)
-
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    @override
-    def predict_messages(
-        self,
-        messages: list[BaseMessage],
-        *,
-        stop: Optional[Sequence[str]] = None,
-        **kwargs: Any,
-    ) -> BaseMessage:
-        stop_ = None if stop is None else list(stop)
-        return self(messages, stop=stop_, **kwargs)
-
-    @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
-    @override
-    async def apredict(
-        self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
-    ) -> str:
-        stop_ = None if stop is None else list(stop)
-        result = await self._call_async(
-            [HumanMessage(content=text)], stop=stop_, **kwargs
-        )
-        if isinstance(result.content, str):
-            return result.content
-        msg = "Cannot use predict when output is not a string."
-        raise ValueError(msg)
-
-    @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
-    @override
-    async def apredict_messages(
-        self,
-        messages: list[BaseMessage],
-        *,
-        stop: Optional[Sequence[str]] = None,
-        **kwargs: Any,
-    ) -> BaseMessage:
-        stop_ = None if stop is None else list(stop)
-        return await self._call_async(messages, stop=stop_, **kwargs)
-
     @property
     @abstractmethod
     def _llm_type(self) -> str:

libs/core/langchain_core/language_models/llms.py

@@ -7,7 +7,6 @@ import functools
 import inspect
 import json
 import logging
-import warnings
 from abc import ABC, abstractmethod
 from collections.abc import AsyncIterator, Iterator, Sequence
 from pathlib import Path
@@ -21,7 +20,7 @@ from typing import (
 )
 
 import yaml
-from pydantic import ConfigDict, Field, model_validator
+from pydantic import ConfigDict
 from tenacity import (
     RetryCallState,
     before_sleep_log,
@@ -33,7 +32,6 @@ from tenacity import (
 )
 from typing_extensions import override
 
-from langchain_core._api import deprecated
 from langchain_core.caches import BaseCache
 from langchain_core.callbacks import (
     AsyncCallbackManager,
@@ -51,10 +49,7 @@ from langchain_core.language_models.base import (
 )
 from langchain_core.load import dumpd
 from langchain_core.messages import (
-    AIMessage,
-    BaseMessage,
     convert_to_messages,
-    get_buffer_string,
 )
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult, RunInfo
 from langchain_core.prompt_values import ChatPromptValue, PromptValue, StringPromptValue
@@ -296,26 +291,10 @@ class BaseLLM(BaseLanguageModel[str], ABC):
     It should take in a prompt and return a string.
     """
 
-    callback_manager: Optional[BaseCallbackManager] = Field(default=None, exclude=True)
-    """[DEPRECATED]"""
-
     model_config = ConfigDict(
         arbitrary_types_allowed=True,
     )
 
-    @model_validator(mode="before")
-    @classmethod
-    def raise_deprecation(cls, values: dict) -> Any:
-        """Raise deprecation warning if callback_manager is used."""
-        if values.get("callback_manager") is not None:
-            warnings.warn(
-                "callback_manager is deprecated. Please use callbacks instead.",
-                DeprecationWarning,
-                stacklevel=5,
-            )
-            values["callbacks"] = values.pop("callback_manager", None)
-        return values
-
     @functools.cached_property
     def _serialized(self) -> dict[str, Any]:
         return dumpd(self)
@@ -1308,56 +1287,6 @@ class BaseLLM(BaseLanguageModel[str], ABC):
         generations = [existing_prompts[i] for i in range(len(prompts))]
         return LLMResult(generations=generations, llm_output=llm_output, run=run_info)
 
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    def __call__(
-        self,
-        prompt: str,
-        stop: Optional[list[str]] = None,
-        callbacks: Callbacks = None,
-        *,
-        tags: Optional[list[str]] = None,
-        metadata: Optional[dict[str, Any]] = None,
-        **kwargs: Any,
-    ) -> str:
-        """Check Cache and run the LLM on the given prompt and input.
-
-        Args:
-            prompt: The prompt to generate from.
-            stop: Stop words to use when generating. Model output is cut off at the
-                first occurrence of any of these substrings.
-            callbacks: Callbacks to pass through. Used for executing additional
-                functionality, such as logging or streaming, throughout generation.
-            tags: List of tags to associate with the prompt.
-            metadata: Metadata to associate with the prompt.
-            **kwargs: Arbitrary additional keyword arguments. These are usually passed
-                to the model provider API call.
-
-        Returns:
-            The generated text.
-
-        Raises:
-            ValueError: If the prompt is not a string.
-        """
-        if not isinstance(prompt, str):
-            msg = (
-                "Argument `prompt` is expected to be a string. Instead found "
-                f"{type(prompt)}. If you want to run the LLM on multiple prompts, use "
-                "`generate` instead."
-            )
-            raise ValueError(msg)  # noqa: TRY004
-        return (
-            self.generate(
-                [prompt],
-                stop=stop,
-                callbacks=callbacks,
-                tags=tags,
-                metadata=metadata,
-                **kwargs,
-            )
-            .generations[0][0]
-            .text
-        )
-
     async def _call_async(
         self,
         prompt: str,
@@ -1379,50 +1308,6 @@ class BaseLLM(BaseLanguageModel[str], ABC):
         )
         return result.generations[0][0].text
 
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    @override
-    def predict(
-        self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
-    ) -> str:
-        stop_ = None if stop is None else list(stop)
-        return self(text, stop=stop_, **kwargs)
-
-    @deprecated("0.1.7", alternative="invoke", removal="1.0")
-    @override
-    def predict_messages(
-        self,
-        messages: list[BaseMessage],
-        *,
-        stop: Optional[Sequence[str]] = None,
-        **kwargs: Any,
-    ) -> BaseMessage:
-        text = get_buffer_string(messages)
-        stop_ = None if stop is None else list(stop)
-        content = self(text, stop=stop_, **kwargs)
-        return AIMessage(content=content)
-
-    @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
-    @override
-    async def apredict(
-        self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
-    ) -> str:
-        stop_ = None if stop is None else list(stop)
-        return await self._call_async(text, stop=stop_, **kwargs)
-
-    @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
-    @override
-    async def apredict_messages(
-        self,
-        messages: list[BaseMessage],
-        *,
-        stop: Optional[Sequence[str]] = None,
-        **kwargs: Any,
-    ) -> BaseMessage:
-        text = get_buffer_string(messages)
-        stop_ = None if stop is None else list(stop)
-        content = await self._call_async(text, stop=stop_, **kwargs)
-        return AIMessage(content=content)
-
     def __str__(self) -> str:
         """Return a string representation of the object for printing."""
         cls_name = f"\033[1m{self.__class__.__name__}\033[0m"

libs/core/langchain_core/load/mapping.py

@@ -413,11 +413,10 @@ SERIALIZABLE_MAPPING: dict[tuple[str, ...], tuple[str, ...]] = {
         "few_shot_with_templates",
         "FewShotPromptWithTemplates",
     ),
-    ("langchain", "prompts", "pipeline", "PipelinePromptTemplate"): (
+    ("langchain", "prompts", "pipeline"): (
         "langchain_core",
         "prompts",
         "pipeline",
-        "PipelinePromptTemplate",
     ),
     ("langchain", "prompts", "base", "StringPromptTemplate"): (
         "langchain_core",
@@ -846,11 +845,10 @@ OLD_CORE_NAMESPACES_MAPPING: dict[tuple[str, ...], tuple[str, ...]] = {
         "few_shot_with_templates",
         "FewShotPromptWithTemplates",
     ),
-    ("langchain_core", "prompts", "pipeline", "PipelinePromptTemplate"): (
+    ("langchain_core", "prompts", "pipeline"): (
         "langchain_core",
         "prompts",
         "pipeline",
-        "PipelinePromptTemplate",
     ),
     ("langchain_core", "prompts", "string", "StringPromptTemplate"): (
         "langchain_core",

libs/core/langchain_core/messages/utils.py

@@ -1045,6 +1045,7 @@ def convert_to_openai_messages(
     messages: Union[MessageLikeRepresentation, Sequence[MessageLikeRepresentation]],
     *,
     text_format: Literal["string", "block"] = "string",
+    include_id: bool = False,
 ) -> Union[dict, list[dict]]:
     """Convert LangChain messages into OpenAI message dicts.
 
@@ -1062,6 +1063,8 @@ def convert_to_openai_messages(
                     If a message has a string content, this is turned into a list
                     with a single content block of type ``'text'``. If a message has
                     content blocks these are left as is.
+        include_id: Whether to include message ids in the openai messages, if they
+                    are present in the source messages.
 
     Raises:
         ValueError: if an unrecognized ``text_format`` is specified, or if a message
@@ -1150,6 +1153,8 @@ def convert_to_openai_messages(
             oai_msg["refusal"] = message.additional_kwargs["refusal"]
         if isinstance(message, ToolMessage):
             oai_msg["tool_call_id"] = message.tool_call_id
+        if include_id and message.id:
+            oai_msg["id"] = message.id
 
         if not message.content:
             content = "" if text_format == "string" else []

libs/core/langchain_core/prompts/__init__.py

@@ -8,8 +8,7 @@ from multiple components and prompt values. Prompt classes and functions make co
 
 .. code-block::
 
-    BasePromptTemplate --> PipelinePromptTemplate
-                           StringPromptTemplate --> PromptTemplate
+    BasePromptTemplate --> StringPromptTemplate --> PromptTemplate
                                                     FewShotPromptTemplate
                                                     FewShotPromptWithTemplates
                            BaseChatPromptTemplate --> AutoGPTPrompt
@@ -53,7 +52,6 @@ if TYPE_CHECKING:
         FewShotPromptWithTemplates,
     )
     from langchain_core.prompts.loading import load_prompt
-    from langchain_core.prompts.pipeline import PipelinePromptTemplate
     from langchain_core.prompts.prompt import PromptTemplate
     from langchain_core.prompts.string import (
         StringPromptTemplate,
@@ -75,7 +73,6 @@ __all__ = (
     "FewShotPromptWithTemplates",
     "HumanMessagePromptTemplate",
     "MessagesPlaceholder",
-    "PipelinePromptTemplate",
     "PromptTemplate",
     "StringPromptTemplate",
     "SystemMessagePromptTemplate",
@@ -104,7 +101,6 @@ _dynamic_imports = {
     "FewShotPromptTemplate": "few_shot",
     "FewShotPromptWithTemplates": "few_shot_with_templates",
     "load_prompt": "loading",
-    "PipelinePromptTemplate": "pipeline",
     "PromptTemplate": "prompt",
     "StringPromptTemplate": "string",
     "check_valid_template": "string",

libs/core/langchain_core/prompts/chat.py

@@ -24,7 +24,6 @@ from pydantic import (
 )
 from typing_extensions import Self, override
 
-from langchain_core._api import deprecated
 from langchain_core.messages import (
     AIMessage,
     AnyMessage,
@@ -262,14 +261,12 @@ class BaseStringMessagePromptTemplate(BaseMessagePromptTemplate, ABC):
     def from_template_file(
         cls,
         template_file: Union[str, Path],
-        input_variables: list[str],  # noqa: ARG003  # Deprecated
         **kwargs: Any,
     ) -> Self:
         """Create a class from a template file.
 
         Args:
             template_file: path to a template file. String or Path.
-            input_variables: list of input variables.
             **kwargs: keyword arguments to pass to the constructor.
 
         Returns:
@@ -1105,41 +1102,6 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
         message = HumanMessagePromptTemplate(prompt=prompt_template)
         return cls.from_messages([message])
 
-    @classmethod
-    @deprecated("0.0.1", alternative="from_messages", pending=True)
-    def from_role_strings(
-        cls, string_messages: list[tuple[str, str]]
-    ) -> ChatPromptTemplate:
-        """Create a chat prompt template from a list of (role, template) tuples.
-
-        Args:
-            string_messages: list of (role, template) tuples.
-
-        Returns:
-            a chat prompt template.
-        """
-        return cls(
-            messages=[
-                ChatMessagePromptTemplate.from_template(template, role=role)
-                for role, template in string_messages
-            ]
-        )
-
-    @classmethod
-    @deprecated("0.0.1", alternative="from_messages", pending=True)
-    def from_strings(
-        cls, string_messages: list[tuple[type[BaseMessagePromptTemplate], str]]
-    ) -> ChatPromptTemplate:
-        """Create a chat prompt template from a list of (role class, template) tuples.
-
-        Args:
-            string_messages: list of (role class, template) tuples.
-
-        Returns:
-            a chat prompt template.
-        """
-        return cls.from_messages(string_messages)
-
     @classmethod
     def from_messages(
         cls,

libs/core/langchain_core/prompts/pipeline.py

@@ -1,138 +0,0 @@
-"""[DEPRECATED] Pipeline prompt template."""
-
-from typing import Any
-
-from pydantic import model_validator
-
-from langchain_core._api.deprecation import deprecated
-from langchain_core.prompt_values import PromptValue
-from langchain_core.prompts.base import BasePromptTemplate
-from langchain_core.prompts.chat import BaseChatPromptTemplate
-
-
-def _get_inputs(inputs: dict, input_variables: list[str]) -> dict:
-    return {k: inputs[k] for k in input_variables}
-
-
-@deprecated(
-    since="0.3.22",
-    removal="1.0",
-    message=(
-        "This class is deprecated in favor of chaining individual prompts together."
-    ),
-)
-class PipelinePromptTemplate(BasePromptTemplate):
-    """Pipeline prompt template.
-
-    This has been deprecated in favor of chaining individual prompts together in your
-    code; e.g. using a for loop, you could do:
-
-    .. code-block:: python
-
-        my_input = {"key": "value"}
-        for name, prompt in pipeline_prompts:
-            my_input[name] = prompt.invoke(my_input).to_string()
-        my_output = final_prompt.invoke(my_input)
-
-    Prompt template for composing multiple prompt templates together.
-
-    This can be useful when you want to reuse parts of prompts.
-
-    A PipelinePrompt consists of two main parts:
-
-    - final_prompt: This is the final prompt that is returned
-    - pipeline_prompts: This is a list of tuples, consisting
-      of a string (``name``) and a Prompt Template.
-      Each PromptTemplate will be formatted and then passed
-      to future prompt templates as a variable with
-      the same name as ``name``
-
-    """
-
-    final_prompt: BasePromptTemplate
-    """The final prompt that is returned."""
-    pipeline_prompts: list[tuple[str, BasePromptTemplate]]
-    """A list of tuples, consisting of a string (``name``) and a Prompt Template."""
-
-    @classmethod
-    def get_lc_namespace(cls) -> list[str]:
-        """Get the namespace of the langchain object.
-
-        Returns:
-            ``["langchain", "prompts", "pipeline"]``
-        """
-        return ["langchain", "prompts", "pipeline"]
-
-    @model_validator(mode="before")
-    @classmethod
-    def get_input_variables(cls, values: dict) -> Any:
-        """Get input variables."""
-        created_variables = set()
-        all_variables = set()
-        for k, prompt in values["pipeline_prompts"]:
-            created_variables.add(k)
-            all_variables.update(prompt.input_variables)
-        values["input_variables"] = list(all_variables.difference(created_variables))
-        return values
-
-    def format_prompt(self, **kwargs: Any) -> PromptValue:
-        """Format the prompt with the inputs.
-
-        Args:
-            kwargs: Any arguments to be passed to the prompt template.
-
-        Returns:
-            A formatted string.
-        """
-        for k, prompt in self.pipeline_prompts:
-            inputs = _get_inputs(kwargs, prompt.input_variables)
-            if isinstance(prompt, BaseChatPromptTemplate):
-                kwargs[k] = prompt.format_messages(**inputs)
-            else:
-                kwargs[k] = prompt.format(**inputs)
-        inputs = _get_inputs(kwargs, self.final_prompt.input_variables)
-        return self.final_prompt.format_prompt(**inputs)
-
-    async def aformat_prompt(self, **kwargs: Any) -> PromptValue:
-        """Async format the prompt with the inputs.
-
-        Args:
-            kwargs: Any arguments to be passed to the prompt template.
-
-        Returns:
-            A formatted string.
-        """
-        for k, prompt in self.pipeline_prompts:
-            inputs = _get_inputs(kwargs, prompt.input_variables)
-            if isinstance(prompt, BaseChatPromptTemplate):
-                kwargs[k] = await prompt.aformat_messages(**inputs)
-            else:
-                kwargs[k] = await prompt.aformat(**inputs)
-        inputs = _get_inputs(kwargs, self.final_prompt.input_variables)
-        return await self.final_prompt.aformat_prompt(**inputs)
-
-    def format(self, **kwargs: Any) -> str:
-        """Format the prompt with the inputs.
-
-        Args:
-            kwargs: Any arguments to be passed to the prompt template.
-
-        Returns:
-            A formatted string.
-        """
-        return self.format_prompt(**kwargs).to_string()
-
-    async def aformat(self, **kwargs: Any) -> str:
-        """Async format the prompt with the inputs.
-
-        Args:
-            kwargs: Any arguments to be passed to the prompt template.
-
-        Returns:
-            A formatted string.
-        """
-        return (await self.aformat_prompt(**kwargs)).to_string()
-
-    @property
-    def _prompt_type(self) -> str:
-        raise ValueError

libs/core/langchain_core/prompts/prompt.py

@@ -2,7 +2,6 @@
 
 from __future__ import annotations
 
-import warnings
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Optional, Union
 
@@ -235,7 +234,6 @@ class PromptTemplate(StringPromptTemplate):
     def from_file(
         cls,
         template_file: Union[str, Path],
-        input_variables: Optional[list[str]] = None,
         encoding: Optional[str] = None,
         **kwargs: Any,
     ) -> PromptTemplate:
@@ -243,23 +241,13 @@ class PromptTemplate(StringPromptTemplate):
 
         Args:
             template_file: The path to the file containing the prompt template.
-            input_variables: [DEPRECATED] A list of variable names the final prompt
-                template will expect. Defaults to None.
             encoding: The encoding system for opening the template file.
                 If not provided, will use the OS default.
 
-        input_variables is ignored as from_file now delegates to from_template().
-
         Returns:
             The prompt loaded from the file.
         """
         template = Path(template_file).read_text(encoding=encoding)
-        if input_variables:
-            warnings.warn(
-                "`input_variables' is deprecated and ignored.",
-                DeprecationWarning,
-                stacklevel=2,
-            )
         return cls.from_template(template=template, **kwargs)
 
     @classmethod

libs/core/langchain_core/tools/base.py

@@ -31,7 +31,6 @@ from pydantic import (
     PydanticDeprecationWarning,
     SkipValidation,
     ValidationError,
-    model_validator,
     validate_arguments,
 )
 from pydantic.v1 import BaseModel as BaseModelV1
@@ -39,10 +38,8 @@ from pydantic.v1 import ValidationError as ValidationErrorV1
 from pydantic.v1 import validate_arguments as validate_arguments_v1
 from typing_extensions import override
 
-from langchain_core._api import deprecated
 from langchain_core.callbacks import (
     AsyncCallbackManager,
-    BaseCallbackManager,
     CallbackManager,
     Callbacks,
 )
@@ -464,15 +461,6 @@ class ChildTool(BaseTool):
     callbacks: Callbacks = Field(default=None, exclude=True)
     """Callbacks to be called during tool execution."""
 
-    callback_manager: Optional[BaseCallbackManager] = deprecated(
-        name="callback_manager", since="0.1.7", removal="1.0", alternative="callbacks"
-    )(
-        Field(
-            default=None,
-            exclude=True,
-            description="Callback manager to add to the run trace.",
-        )
-    )
     tags: Optional[list[str]] = None
     """Optional list of tags associated with the tool. Defaults to None.
     These tags will be associated with each call to this tool,
@@ -700,26 +688,6 @@ class ChildTool(BaseTool):
             }
         return tool_input
 
-    @model_validator(mode="before")
-    @classmethod
-    def raise_deprecation(cls, values: dict) -> Any:
-        """Raise deprecation warning if callback_manager is used.
-
-        Args:
-            values: The values to validate.
-
-        Returns:
-            The validated values.
-        """
-        if values.get("callback_manager") is not None:
-            warnings.warn(
-                "callback_manager is deprecated. Please use callbacks instead.",
-                DeprecationWarning,
-                stacklevel=6,
-            )
-            values["callbacks"] = values.pop("callback_manager", None)
-        return values
-
     @abstractmethod
     def _run(self, *args: Any, **kwargs: Any) -> Any:
         """Use the tool.
@@ -1011,19 +979,6 @@ class ChildTool(BaseTool):
         await run_manager.on_tool_end(output, color=color, name=self.name, **kwargs)
         return output
 
-    @deprecated("0.1.47", alternative="invoke", removal="1.0")
-    def __call__(self, tool_input: str, callbacks: Callbacks = None) -> str:
-        """Make tool callable (deprecated).
-
-        Args:
-            tool_input: The input to the tool.
-            callbacks: Callbacks to use during execution.
-
-        Returns:
-            The tool's output.
-        """
-        return self.run(tool_input, callbacks=callbacks)
-
 
 def _is_tool_call(x: Any) -> bool:
     """Check if the input is a tool call dictionary.

libs/core/langchain_core/tracers/context.py

@@ -27,7 +27,6 @@ if TYPE_CHECKING:
 
     from langchain_core.callbacks.base import BaseCallbackHandler, Callbacks
     from langchain_core.callbacks.manager import AsyncCallbackManager, CallbackManager
-    from langchain_core.tracers.schemas import TracerSessionV1
 
 # for backwards partial compatibility if this is imported by users but unused
 tracing_callback_var: Any = None
@@ -39,21 +38,6 @@ run_collector_var: ContextVar[Optional[RunCollectorCallbackHandler]] = ContextVa
 )
 
 
-@contextmanager
-def tracing_enabled(
-    session_name: str = "default",  # noqa: ARG001
-) -> Generator[TracerSessionV1, None, None]:
-    """Throw an error because this has been replaced by ``tracing_v2_enabled``.
-
-    Raises:
-        RuntimeError: Always, because this function is deprecated.
-    """
-    msg = (
-        "tracing_enabled is no longer supported. Please use tracing_enabled_v2 instead."
-    )
-    raise RuntimeError(msg)
-
-
 @contextmanager
 def tracing_v2_enabled(
     project_name: Optional[str] = None,

libs/core/langchain_core/tracers/langchain_v1.py

@@ -1,31 +0,0 @@
-"""This module is deprecated and will be removed in a future release.
-
-Please use LangChainTracer instead.
-"""
-
-from typing import Any
-
-
-def get_headers(*args: Any, **kwargs: Any) -> Any:  # noqa: ARG001
-    """Throw an error because this has been replaced by get_headers.
-
-    Raises:
-        RuntimeError: Always, because this function is deprecated.
-    """
-    msg = (
-        "get_headers for LangChainTracerV1 is no longer supported. "
-        "Please use LangChainTracer instead."
-    )
-    raise RuntimeError(msg)
-
-
-def LangChainTracerV1(*args: Any, **kwargs: Any) -> Any:  # noqa: N802,ARG001
-    """Throw an error because this has been replaced by ``LangChainTracer``.
-
-    Raises:
-        RuntimeError: Always, because this class is deprecated.
-    """
-    msg = (
-        "LangChainTracerV1 is no longer supported. Please use LangChainTracer instead."
-    )
-    raise RuntimeError(msg)

libs/core/langchain_core/utils/__init__.py

@@ -21,7 +21,6 @@ if TYPE_CHECKING:
         print_text,
     )
     from langchain_core.utils.iter import batch_iterate
-    from langchain_core.utils.loading import try_load_from_hub
     from langchain_core.utils.pydantic import pre_init
     from langchain_core.utils.strings import (
         comma_list,
@@ -68,7 +67,6 @@ __all__ = (
     "secret_from_env",
     "stringify_dict",
     "stringify_value",
-    "try_load_from_hub",
     "xor_args",
 )
 
@@ -84,7 +82,6 @@ _dynamic_imports = {
     "get_colored_text": "input",
     "print_text": "input",
     "batch_iterate": "iter",
-    "try_load_from_hub": "loading",
     "pre_init": "pydantic",
     "comma_list": "strings",
     "sanitize_for_postgres": "strings",

libs/core/langchain_core/utils/loading.py

@@ -1,35 +0,0 @@
-"""Utilities for loading configurations from langchain_core-hub."""
-
-import warnings
-from typing import Any
-
-from langchain_core._api.deprecation import deprecated
-
-
-@deprecated(
-    since="0.1.30",
-    removal="1.0",
-    message=(
-        "Using the hwchase17/langchain-hub "
-        "repo for prompts is deprecated. Please use "
-        "<https://smith.langchain.com/hub> instead."
-    ),
-)
-def try_load_from_hub(
-    *args: Any,  # noqa: ARG001
-    **kwargs: Any,  # noqa: ARG001
-) -> Any:
-    """[DEPRECATED] Try to load from the old Hub.
-
-    Returns:
-        None always, indicating that we shouldn't load from the old hub.
-    """
-    warnings.warn(
-        "Loading from the deprecated github-based Hub is no longer supported. "
-        "Please use the new LangChain Hub at https://smith.langchain.com/hub instead.",
-        DeprecationWarning,
-        stacklevel=2,
-    )
-    # return None, which indicates that we shouldn't load from old hub
-    # and might just be a filepath for e.g. load_chain
-    return None

libs/core/langchain_core/vectorstores/in_memory.py

@@ -14,7 +14,6 @@ from typing import (
 
 from typing_extensions import override
 
-from langchain_core._api import deprecated
 from langchain_core.documents import Document
 from langchain_core.load import dumpd, load
 from langchain_core.vectorstores import VectorStore
@@ -25,7 +24,6 @@ if TYPE_CHECKING:
     from collections.abc import Iterator, Sequence
 
     from langchain_core.embeddings import Embeddings
-    from langchain_core.indexing import UpsertResponse
 
 try:
     import numpy as np
@@ -281,76 +279,6 @@ class InMemoryVectorStore(VectorStore):
                 )
         return documents
 
-    @deprecated(
-        alternative="VectorStore.add_documents",
-        message=(
-            "This was a beta API that was added in 0.2.11. It'll be removed in 0.3.0."
-        ),
-        since="0.2.29",
-        removal="1.0",
-    )
-    def upsert(self, items: Sequence[Document], /, **_kwargs: Any) -> UpsertResponse:
-        """[DEPRECATED] Upsert documents into the store.
-
-        Args:
-            items: The documents to upsert.
-
-        Returns:
-            The upsert response.
-        """
-        vectors = self.embedding.embed_documents([item.page_content for item in items])
-        ids = []
-        for item, vector in zip(items, vectors):
-            doc_id = item.id or str(uuid.uuid4())
-            ids.append(doc_id)
-            self.store[doc_id] = {
-                "id": doc_id,
-                "vector": vector,
-                "text": item.page_content,
-                "metadata": item.metadata,
-            }
-        return {
-            "succeeded": ids,
-            "failed": [],
-        }
-
-    @deprecated(
-        alternative="VectorStore.aadd_documents",
-        message=(
-            "This was a beta API that was added in 0.2.11. It'll be removed in 0.3.0."
-        ),
-        since="0.2.29",
-        removal="1.0",
-    )
-    async def aupsert(
-        self, items: Sequence[Document], /, **_kwargs: Any
-    ) -> UpsertResponse:
-        """[DEPRECATED] Upsert documents into the store.
-
-        Args:
-            items: The documents to upsert.
-
-        Returns:
-            The upsert response.
-        """
-        vectors = await self.embedding.aembed_documents(
-            [item.page_content for item in items]
-        )
-        ids = []
-        for item, vector in zip(items, vectors):
-            doc_id = item.id or str(uuid.uuid4())
-            ids.append(doc_id)
-            self.store[doc_id] = {
-                "id": doc_id,
-                "vector": vector,
-                "text": item.page_content,
-                "metadata": item.metadata,
-            }
-        return {
-            "succeeded": ids,
-            "failed": [],
-        }
-
     @override
     async def aget_by_ids(self, ids: Sequence[str], /) -> list[Document]:
         """Async get documents by their ids.

libs/core/tests/unit_tests/messages/test_utils.py

@@ -882,10 +882,21 @@ def test_convert_to_openai_messages_string() -> None:
 
 
 def test_convert_to_openai_messages_single_message() -> None:
-    message = HumanMessage(content="Hello")
+    message: BaseMessage = HumanMessage(content="Hello")
     result = convert_to_openai_messages(message)
     assert result == {"role": "user", "content": "Hello"}
 
+    # Test IDs
+    result = convert_to_openai_messages(message, include_id=True)
+    assert result == {"role": "user", "content": "Hello"}  # no ID
+
+    message = AIMessage(content="Hello", id="resp_123")
+    result = convert_to_openai_messages(message)
+    assert result == {"role": "assistant", "content": "Hello"}
+
+    result = convert_to_openai_messages(message, include_id=True)
+    assert result == {"role": "assistant", "content": "Hello", "id": "resp_123"}
+
 
 def test_convert_to_openai_messages_multiple_messages() -> None:
     messages = [

libs/core/tests/unit_tests/prompts/test_chat.py

@@ -8,14 +8,10 @@ from packaging import version
 from pydantic import ValidationError
 from syrupy.assertion import SnapshotAssertion
 
-from langchain_core._api.deprecation import (
-    LangChainPendingDeprecationWarning,
-)
 from langchain_core.load import dumpd, load
 from langchain_core.messages import (
     AIMessage,
     BaseMessage,
-    ChatMessage,
     HumanMessage,
     SystemMessage,
     ToolMessage,
@@ -191,7 +187,6 @@ def test_message_prompt_template_from_template_file() -> None:
     )
     actual = ChatMessagePromptTemplate.from_template_file(
         Path(__file__).parent.parent / "data" / "prompt_file.txt",
-        ["question"],
         role="human",
     )
     assert expected == actual
@@ -459,32 +454,6 @@ def test_chat_valid_infer_variables() -> None:
     assert prompt.partial_variables == {"formatins": "some structure"}
 
 
-async def test_chat_from_role_strings() -> None:
-    """Test instantiation of chat template from role strings."""
-    with pytest.warns(LangChainPendingDeprecationWarning):
-        template = ChatPromptTemplate.from_role_strings(
-            [
-                ("system", "You are a bot."),
-                ("assistant", "hello!"),
-                ("human", "{question}"),
-                ("other", "{quack}"),
-            ]
-        )
-
-    expected = [
-        ChatMessage(content="You are a bot.", role="system"),
-        ChatMessage(content="hello!", role="assistant"),
-        ChatMessage(content="How are you?", role="human"),
-        ChatMessage(content="duck", role="other"),
-    ]
-
-    messages = template.format_messages(question="How are you?", quack="duck")
-    assert messages == expected
-
-    messages = await template.aformat_messages(question="How are you?", quack="duck")
-    assert messages == expected
-
-
 @pytest.mark.parametrize(
     ("args", "expected"),
     [

libs/core/tests/unit_tests/prompts/test_imports.py

@@ -14,7 +14,6 @@ EXPECTED_ALL = [
     "aformat_document",
     "HumanMessagePromptTemplate",
     "MessagesPlaceholder",
-    "PipelinePromptTemplate",
     "PromptTemplate",
     "StringPromptTemplate",
     "SystemMessagePromptTemplate",

libs/core/tests/unit_tests/prompts/test_pipeline_prompt.py

@@ -1,68 +0,0 @@
-import pytest
-
-from langchain_core.prompts.chat import ChatPromptTemplate, MessagesPlaceholder
-from langchain_core.prompts.pipeline import PipelinePromptTemplate
-from langchain_core.prompts.prompt import PromptTemplate
-
-# Suppress deprecation warnings for PipelinePromptTemplate since we're testing the
-# deprecated functionality intentionally to ensure it still works correctly
-
-
-@pytest.mark.filterwarnings(
-    "ignore:This class is deprecated"
-    ":langchain_core._api.deprecation.LangChainDeprecationWarning"
-)
-def test_get_input_variables() -> None:
-    prompt_a = PromptTemplate.from_template("{foo}")
-    prompt_b = PromptTemplate.from_template("{bar}")
-    pipeline_prompt = PipelinePromptTemplate(  # type: ignore[call-arg]
-        final_prompt=prompt_b, pipeline_prompts=[("bar", prompt_a)]
-    )
-    assert pipeline_prompt.input_variables == ["foo"]
-
-
-@pytest.mark.filterwarnings(
-    "ignore:This class is deprecated"
-    ":langchain_core._api.deprecation.LangChainDeprecationWarning"
-)
-def test_simple_pipeline() -> None:
-    prompt_a = PromptTemplate.from_template("{foo}")
-    prompt_b = PromptTemplate.from_template("{bar}")
-    pipeline_prompt = PipelinePromptTemplate(  # type: ignore[call-arg]
-        final_prompt=prompt_b, pipeline_prompts=[("bar", prompt_a)]
-    )
-    output = pipeline_prompt.format(foo="jim")
-    assert output == "jim"
-
-
-@pytest.mark.filterwarnings(
-    "ignore:This class is deprecated"
-    ":langchain_core._api.deprecation.LangChainDeprecationWarning"
-)
-def test_multi_variable_pipeline() -> None:
-    prompt_a = PromptTemplate.from_template("{foo}")
-    prompt_b = PromptTemplate.from_template("okay {bar} {baz}")
-    pipeline_prompt = PipelinePromptTemplate(  # type: ignore[call-arg]
-        final_prompt=prompt_b, pipeline_prompts=[("bar", prompt_a)]
-    )
-    output = pipeline_prompt.format(foo="jim", baz="deep")
-    assert output == "okay jim deep"
-
-
-@pytest.mark.filterwarnings(
-    "ignore:This class is deprecated"
-    ":langchain_core._api.deprecation.LangChainDeprecationWarning"
-)
-async def test_partial_with_chat_prompts() -> None:
-    prompt_a = ChatPromptTemplate(
-        input_variables=["foo"], messages=[MessagesPlaceholder(variable_name="foo")]
-    )
-    prompt_b = ChatPromptTemplate.from_template("jim {bar}")
-    pipeline_prompt = PipelinePromptTemplate(  # type: ignore[call-arg]
-        final_prompt=prompt_a, pipeline_prompts=[("foo", prompt_b)]
-    )
-    assert pipeline_prompt.input_variables == ["bar"]
-    output = pipeline_prompt.format_prompt(bar="okay")
-    assert output.to_messages()[0].content == "jim okay"
-    output = await pipeline_prompt.aformat_prompt(bar="okay")
-    assert output.to_messages()[0].content == "jim okay"

libs/core/tests/unit_tests/runnables/test_history.py

@@ -32,10 +32,9 @@ from tests.unit_tests.pydantic_utils import _schema
 def test_interfaces() -> None:
     history = InMemoryChatMessageHistory()
     history.add_message(SystemMessage(content="system"))
-    history.add_user_message("human 1")
-    history.add_ai_message("ai")
-    history.add_message(HumanMessage(content="human 2"))
-    assert str(history) == "System: system\nHuman: human 1\nAI: ai\nHuman: human 2"
+    history.add_message(HumanMessage(content="human 1"))
+    history.add_message(AIMessage(content="ai"))
+    assert str(history) == "System: system\nHuman: human 1\nAI: ai"
 
 
 def _get_get_session_history(

libs/core/tests/unit_tests/utils/test_imports.py

@@ -16,7 +16,6 @@ EXPECTED_ALL = [
     "print_text",
     "raise_for_status_with_text",
     "xor_args",
-    "try_load_from_hub",
     "image",
     "build_extra_kwargs",
     "get_from_dict_or_env",

libs/langchain/Makefile

@@ -36,7 +36,7 @@ test_watch_extended:
 integration_tests:
 	uv run --group test --group test_integration pytest tests/integration_tests
 
-check_imports: $(shell find langchain -name '*.py')
+check_imports: $(shell find langchain_classic -name '*.py')
 	uv run python ./scripts/check_imports.py $^
 
 ######################
@@ -48,7 +48,7 @@ PYTHON_FILES=.
 MYPY_CACHE=.mypy_cache
 lint format: PYTHON_FILES=.
 lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/langchain --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
-lint_package: PYTHON_FILES=langchain
+lint_package: PYTHON_FILES=langchain_classic
 lint_tests: PYTHON_FILES=tests
 lint_tests: MYPY_CACHE=.mypy_cache_test
 

libs/langchain/README.md

@@ -13,7 +13,7 @@ To help you ship LangChain apps to production faster, check out [LangSmith](http
 
 ## Quick Install
 
-`pip install langchain`
+`pip install langchain-classic`
 
 ## 🤔 What is this?
 

libs/langchain/langchain/agents/agent_toolkits/conversational_retrieval/tool.py

@@ -1,3 +0,0 @@
-from langchain.tools.retriever import create_retriever_tool
-
-__all__ = ["create_retriever_tool"]

libs/langchain/langchain/agents/openai_assistant/__init__.py

@@ -1,3 +0,0 @@
-from langchain.agents.openai_assistant.base import OpenAIAssistantRunnable
-
-__all__ = ["OpenAIAssistantRunnable"]

libs/langchain/langchain/agents/self_ask_with_search/output_parser.py

@@ -1,4 +0,0 @@
-from langchain.agents.output_parsers.self_ask import SelfAskOutputParser
-
-# For backwards compatibility
-__all__ = ["SelfAskOutputParser"]

libs/langchain/langchain/agents/types.py

@@ -1,27 +0,0 @@
-from typing import Union
-
-from langchain.agents.agent import BaseSingleActionAgent
-from langchain.agents.agent_types import AgentType
-from langchain.agents.chat.base import ChatAgent
-from langchain.agents.conversational.base import ConversationalAgent
-from langchain.agents.conversational_chat.base import ConversationalChatAgent
-from langchain.agents.mrkl.base import ZeroShotAgent
-from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
-from langchain.agents.openai_functions_multi_agent.base import OpenAIMultiFunctionsAgent
-from langchain.agents.react.base import ReActDocstoreAgent
-from langchain.agents.self_ask_with_search.base import SelfAskWithSearchAgent
-from langchain.agents.structured_chat.base import StructuredChatAgent
-
-AGENT_TYPE = Union[type[BaseSingleActionAgent], type[OpenAIMultiFunctionsAgent]]
-
-AGENT_TO_CLASS: dict[AgentType, AGENT_TYPE] = {
-    AgentType.ZERO_SHOT_REACT_DESCRIPTION: ZeroShotAgent,
-    AgentType.REACT_DOCSTORE: ReActDocstoreAgent,
-    AgentType.SELF_ASK_WITH_SEARCH: SelfAskWithSearchAgent,
-    AgentType.CONVERSATIONAL_REACT_DESCRIPTION: ConversationalAgent,
-    AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION: ChatAgent,
-    AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION: ConversationalChatAgent,
-    AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION: StructuredChatAgent,
-    AgentType.OPENAI_FUNCTIONS: OpenAIFunctionsAgent,
-    AgentType.OPENAI_MULTI_FUNCTIONS: OpenAIMultiFunctionsAgent,
-}

libs/langchain/langchain/callbacks/tracers/langchain_v1.py

@@ -1,3 +0,0 @@
-from langchain_core.tracers.langchain_v1 import LangChainTracerV1
-
-__all__ = ["LangChainTracerV1"]

libs/langchain/langchain/chains/__init__.py

@@ -1,96 +0,0 @@
-"""**Chains** are easily reusable components linked together.
-
-Chains encode a sequence of calls to components like models, document retrievers,
-other Chains, etc., and provide a simple interface to this sequence.
-
-The Chain interface makes it easy to create apps that are:
-
-    - **Stateful:** add Memory to any Chain to give it state,
-    - **Observable:** pass Callbacks to a Chain to execute additional functionality,
-      like logging, outside the main sequence of component calls,
-    - **Composable:** combine Chains with other components, including other Chains.
-
-**Class hierarchy:**
-
-.. code-block::
-
-    Chain --> <name>Chain  # Examples: LLMChain, MapReduceChain, RouterChain
-"""
-
-from typing import Any
-
-from langchain._api import create_importer
-
-_module_lookup = {
-    "APIChain": "langchain.chains.api.base",
-    "OpenAPIEndpointChain": "langchain_community.chains.openapi.chain",
-    "AnalyzeDocumentChain": "langchain.chains.combine_documents.base",
-    "MapReduceDocumentsChain": "langchain.chains.combine_documents.map_reduce",
-    "MapRerankDocumentsChain": "langchain.chains.combine_documents.map_rerank",
-    "ReduceDocumentsChain": "langchain.chains.combine_documents.reduce",
-    "RefineDocumentsChain": "langchain.chains.combine_documents.refine",
-    "StuffDocumentsChain": "langchain.chains.combine_documents.stuff",
-    "ConstitutionalChain": "langchain.chains.constitutional_ai.base",
-    "ConversationChain": "langchain.chains.conversation.base",
-    "ChatVectorDBChain": "langchain.chains.conversational_retrieval.base",
-    "ConversationalRetrievalChain": "langchain.chains.conversational_retrieval.base",
-    "generate_example": "langchain.chains.example_generator",
-    "FlareChain": "langchain.chains.flare.base",
-    "ArangoGraphQAChain": "langchain_community.chains.graph_qa.arangodb",
-    "GraphQAChain": "langchain_community.chains.graph_qa.base",
-    "GraphCypherQAChain": "langchain_community.chains.graph_qa.cypher",
-    "FalkorDBQAChain": "langchain_community.chains.graph_qa.falkordb",
-    "HugeGraphQAChain": "langchain_community.chains.graph_qa.hugegraph",
-    "KuzuQAChain": "langchain_community.chains.graph_qa.kuzu",
-    "NebulaGraphQAChain": "langchain_community.chains.graph_qa.nebulagraph",
-    "NeptuneOpenCypherQAChain": "langchain_community.chains.graph_qa.neptune_cypher",
-    "NeptuneSparqlQAChain": "langchain_community.chains.graph_qa.neptune_sparql",
-    "OntotextGraphDBQAChain": "langchain_community.chains.graph_qa.ontotext_graphdb",
-    "GraphSparqlQAChain": "langchain_community.chains.graph_qa.sparql",
-    "create_history_aware_retriever": "langchain.chains.history_aware_retriever",
-    "HypotheticalDocumentEmbedder": "langchain.chains.hyde.base",
-    "LLMChain": "langchain.chains.llm",
-    "LLMCheckerChain": "langchain.chains.llm_checker.base",
-    "LLMMathChain": "langchain.chains.llm_math.base",
-    "LLMRequestsChain": "langchain_community.chains.llm_requests",
-    "LLMSummarizationCheckerChain": "langchain.chains.llm_summarization_checker.base",
-    "load_chain": "langchain.chains.loading",
-    "MapReduceChain": "langchain.chains.mapreduce",
-    "OpenAIModerationChain": "langchain.chains.moderation",
-    "NatBotChain": "langchain.chains.natbot.base",
-    "create_citation_fuzzy_match_chain": "langchain.chains.openai_functions",
-    "create_citation_fuzzy_match_runnable": "langchain.chains.openai_functions",
-    "create_extraction_chain": "langchain.chains.openai_functions",
-    "create_extraction_chain_pydantic": "langchain.chains.openai_functions",
-    "create_qa_with_sources_chain": "langchain.chains.openai_functions",
-    "create_qa_with_structure_chain": "langchain.chains.openai_functions",
-    "create_tagging_chain": "langchain.chains.openai_functions",
-    "create_tagging_chain_pydantic": "langchain.chains.openai_functions",
-    "QAGenerationChain": "langchain.chains.qa_generation.base",
-    "QAWithSourcesChain": "langchain.chains.qa_with_sources.base",
-    "RetrievalQAWithSourcesChain": "langchain.chains.qa_with_sources.retrieval",
-    "VectorDBQAWithSourcesChain": "langchain.chains.qa_with_sources.vector_db",
-    "create_retrieval_chain": "langchain.chains.retrieval",
-    "RetrievalQA": "langchain.chains.retrieval_qa.base",
-    "VectorDBQA": "langchain.chains.retrieval_qa.base",
-    "LLMRouterChain": "langchain.chains.router",
-    "MultiPromptChain": "langchain.chains.router",
-    "MultiRetrievalQAChain": "langchain.chains.router",
-    "MultiRouteChain": "langchain.chains.router",
-    "RouterChain": "langchain.chains.router",
-    "SequentialChain": "langchain.chains.sequential",
-    "SimpleSequentialChain": "langchain.chains.sequential",
-    "create_sql_query_chain": "langchain.chains.sql_database.query",
-    "create_structured_output_runnable": "langchain.chains.structured_output",
-    "load_summarize_chain": "langchain.chains.summarize",
-    "TransformChain": "langchain.chains.transform",
-}
-
-importer = create_importer(__package__, module_lookup=_module_lookup)
-
-
-def __getattr__(name: str) -> Any:
-    return importer(name)
-
-
-__all__ = list(_module_lookup.keys())

libs/langchain/langchain/chains/elasticsearch_database/__init__.py

@@ -1,3 +0,0 @@
-from langchain.chains.elasticsearch_database.base import ElasticsearchDatabaseChain
-
-__all__ = ["ElasticsearchDatabaseChain"]

libs/langchain/langchain/chains/openai_tools/__init__.py

@@ -1,3 +0,0 @@
-from langchain.chains.openai_tools.extraction import create_extraction_chain_pydantic
-
-__all__ = ["create_extraction_chain_pydantic"]

libs/langchain/langchain/chains/query_constructor/__init__.py

@@ -1,3 +0,0 @@
-from langchain.chains.query_constructor.base import load_query_constructor_runnable
-
-__all__ = ["load_query_constructor_runnable"]

libs/langchain/langchain/chains/question_answering/__init__.py

@@ -1,6 +0,0 @@
-from langchain.chains.question_answering.chain import LoadingCallable, load_qa_chain
-
-__all__ = [
-    "LoadingCallable",
-    "load_qa_chain",
-]

libs/langchain/langchain/chains/router/__init__.py

@@ -1,12 +0,0 @@
-from langchain.chains.router.base import MultiRouteChain, RouterChain
-from langchain.chains.router.llm_router import LLMRouterChain
-from langchain.chains.router.multi_prompt import MultiPromptChain
-from langchain.chains.router.multi_retrieval_qa import MultiRetrievalQAChain
-
-__all__ = [
-    "LLMRouterChain",
-    "MultiPromptChain",
-    "MultiRetrievalQAChain",
-    "MultiRouteChain",
-    "RouterChain",
-]

libs/langchain/langchain/evaluation/agents/__init__.py

@@ -1,5 +0,0 @@
-"""Chains for evaluating ReAct style agents."""
-
-from langchain.evaluation.agents.trajectory_eval_chain import TrajectoryEvalChain
-
-__all__ = ["TrajectoryEvalChain"]

libs/langchain/langchain/globals.py

@@ -1,180 +0,0 @@
-"""Global values and configuration that apply to all of LangChain."""
-
-import warnings
-from typing import TYPE_CHECKING, Optional
-
-if TYPE_CHECKING:
-    from langchain_core.caches import BaseCache
-
-
-# DO NOT USE THESE VALUES DIRECTLY!
-# Use them only via `get_<X>()` and `set_<X>()` below,
-# or else your code may behave unexpectedly with other uses of these global settings:
-# https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-_verbose: bool = False
-_debug: bool = False
-_llm_cache: Optional["BaseCache"] = None
-
-
-def set_verbose(
-    value: bool,  # noqa: FBT001
-) -> None:
-    """Set a new value for the `verbose` global setting."""
-    import langchain
-
-    # We're about to run some deprecated code, don't report warnings from it.
-    # The user called the correct (non-deprecated) code path and shouldn't get warnings.
-    with warnings.catch_warnings():
-        warnings.filterwarnings(
-            "ignore",
-            message=(
-                "Importing verbose from langchain root module is no longer supported"
-            ),
-        )
-        # N.B.: This is a workaround for an unfortunate quirk of Python's
-        #       module-level `__getattr__()` implementation:
-        # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-        #
-        # Remove it once `langchain.verbose` is no longer supported, and once all users
-        # have migrated to using `set_verbose()` here.
-        langchain.verbose = value
-
-    global _verbose  # noqa: PLW0603
-    _verbose = value
-
-
-def get_verbose() -> bool:
-    """Get the value of the `verbose` global setting."""
-    import langchain
-
-    # We're about to run some deprecated code, don't report warnings from it.
-    # The user called the correct (non-deprecated) code path and shouldn't get warnings.
-    with warnings.catch_warnings():
-        warnings.filterwarnings(
-            "ignore",
-            message=(
-                "Importing verbose from langchain root module is no longer supported"
-            ),
-        )
-        # N.B.: This is a workaround for an unfortunate quirk of Python's
-        #       module-level `__getattr__()` implementation:
-        # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-        #
-        # Remove it once `langchain.verbose` is no longer supported, and once all users
-        # have migrated to using `set_verbose()` here.
-        #
-        # In the meantime, the `verbose` setting is considered True if either the old
-        # or the new value are True. This accommodates users who haven't migrated
-        # to using `set_verbose()` yet. Those users are getting deprecation warnings
-        # directing them to use `set_verbose()` when they import `langchain.verbose`.
-        old_verbose = langchain.verbose
-
-    return _verbose or old_verbose
-
-
-def set_debug(
-    value: bool,  # noqa: FBT001
-) -> None:
-    """Set a new value for the `debug` global setting."""
-    import langchain
-
-    # We're about to run some deprecated code, don't report warnings from it.
-    # The user called the correct (non-deprecated) code path and shouldn't get warnings.
-    with warnings.catch_warnings():
-        warnings.filterwarnings(
-            "ignore",
-            message="Importing debug from langchain root module is no longer supported",
-        )
-        # N.B.: This is a workaround for an unfortunate quirk of Python's
-        #       module-level `__getattr__()` implementation:
-        # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-        #
-        # Remove it once `langchain.debug` is no longer supported, and once all users
-        # have migrated to using `set_debug()` here.
-        langchain.debug = value
-
-    global _debug  # noqa: PLW0603
-    _debug = value
-
-
-def get_debug() -> bool:
-    """Get the value of the `debug` global setting."""
-    import langchain
-
-    # We're about to run some deprecated code, don't report warnings from it.
-    # The user called the correct (non-deprecated) code path and shouldn't get warnings.
-    with warnings.catch_warnings():
-        warnings.filterwarnings(
-            "ignore",
-            message="Importing debug from langchain root module is no longer supported",
-        )
-        # N.B.: This is a workaround for an unfortunate quirk of Python's
-        #       module-level `__getattr__()` implementation:
-        # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-        #
-        # Remove it once `langchain.debug` is no longer supported, and once all users
-        # have migrated to using `set_debug()` here.
-        #
-        # In the meantime, the `debug` setting is considered True if either the old
-        # or the new value are True. This accommodates users who haven't migrated
-        # to using `set_debug()` yet. Those users are getting deprecation warnings
-        # directing them to use `set_debug()` when they import `langchain.debug`.
-        old_debug = langchain.debug
-
-    return _debug or old_debug
-
-
-def set_llm_cache(value: Optional["BaseCache"]) -> None:
-    """Set a new LLM cache, overwriting the previous value, if any."""
-    import langchain
-
-    # We're about to run some deprecated code, don't report warnings from it.
-    # The user called the correct (non-deprecated) code path and shouldn't get warnings.
-    with warnings.catch_warnings():
-        warnings.filterwarnings(
-            "ignore",
-            message=(
-                "Importing llm_cache from langchain root module is no longer supported"
-            ),
-        )
-        # N.B.: This is a workaround for an unfortunate quirk of Python's
-        #       module-level `__getattr__()` implementation:
-        # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-        #
-        # Remove it once `langchain.llm_cache` is no longer supported, and
-        # once all users have migrated to using `set_llm_cache()` here.
-        langchain.llm_cache = value
-
-    global _llm_cache  # noqa: PLW0603
-    _llm_cache = value
-
-
-def get_llm_cache() -> "BaseCache":
-    """Get the value of the `llm_cache` global setting."""
-    import langchain
-
-    # We're about to run some deprecated code, don't report warnings from it.
-    # The user called the correct (non-deprecated) code path and shouldn't get warnings.
-    with warnings.catch_warnings():
-        warnings.filterwarnings(
-            "ignore",
-            message=(
-                "Importing llm_cache from langchain root module is no longer supported"
-            ),
-        )
-        # N.B.: This is a workaround for an unfortunate quirk of Python's
-        #       module-level `__getattr__()` implementation:
-        # https://github.com/langchain-ai/langchain/pull/11311#issuecomment-1743780004
-        #
-        # Remove it once `langchain.llm_cache` is no longer supported, and
-        # once all users have migrated to using `set_llm_cache()` here.
-        #
-        # In the meantime, the `llm_cache` setting returns whichever of
-        # its two backing sources is truthy (not `None` and non-empty),
-        # or the old value if both are falsy. This accommodates users
-        # who haven't migrated to using `set_llm_cache()` yet.
-        # Those users are getting deprecation warnings directing them
-        # to use `set_llm_cache()` when they import `langchain.llm_cache`.
-        old_llm_cache = langchain.llm_cache
-
-    return _llm_cache or old_llm_cache

libs/langchain/langchain/prompts/pipeline.py

@@ -1,3 +0,0 @@
-from langchain_core.prompts.pipeline import PipelinePromptTemplate, _get_inputs
-
-__all__ = ["PipelinePromptTemplate", "_get_inputs"]

libs/langchain/langchain/schema/callbacks/tracers/langchain_v1.py

@@ -1,3 +0,0 @@
-from langchain_core.tracers.langchain_v1 import LangChainTracerV1, get_headers
-
-__all__ = ["LangChainTracerV1", "get_headers"]

libs/langchain/langchain/utilities/loading.py

@@ -1,4 +0,0 @@
-from langchain_core.utils.loading import try_load_from_hub
-
-# For backwards compatibility
-__all__ = ["try_load_from_hub"]

libs/langchain/langchain/utils/loading.py

@@ -1,3 +0,0 @@
-from langchain_core.utils.loading import try_load_from_hub
-
-__all__ = ["try_load_from_hub"]

libs/langchain/langchain_classic/__init__.py

@@ -16,7 +16,7 @@ del metadata  # optional, avoids polluting the results of dir(__package__)
 
 def _warn_on_import(name: str, replacement: Optional[str] = None) -> None:
     """Warn on import of deprecated module."""
-    from langchain._api.interactive_env import is_interactive_env
+    from langchain_classic._api.interactive_env import is_interactive_env
 
     if is_interactive_env():
         # No warnings for interactive environments.
@@ -38,33 +38,35 @@ def _warn_on_import(name: str, replacement: Optional[str] = None) -> None:
         )
 
 
-# Surfaces Deprecation and Pending Deprecation warnings from langchain.
+# Surfaces Deprecation and Pending Deprecation warnings from langchain_classic.
 surface_langchain_deprecation_warnings()
 
 
 def __getattr__(name: str) -> Any:
     if name == "MRKLChain":
-        from langchain.agents import MRKLChain
+        from langchain_classic.agents import MRKLChain
 
-        _warn_on_import(name, replacement="langchain.agents.MRKLChain")
+        _warn_on_import(name, replacement="langchain_classic.agents.MRKLChain")
 
         return MRKLChain
     if name == "ReActChain":
-        from langchain.agents import ReActChain
+        from langchain_classic.agents import ReActChain
 
-        _warn_on_import(name, replacement="langchain.agents.ReActChain")
+        _warn_on_import(name, replacement="langchain_classic.agents.ReActChain")
 
         return ReActChain
     if name == "SelfAskWithSearchChain":
-        from langchain.agents import SelfAskWithSearchChain
+        from langchain_classic.agents import SelfAskWithSearchChain
 
-        _warn_on_import(name, replacement="langchain.agents.SelfAskWithSearchChain")
+        _warn_on_import(
+            name, replacement="langchain_classic.agents.SelfAskWithSearchChain"
+        )
 
         return SelfAskWithSearchChain
     if name == "ConversationChain":
-        from langchain.chains import ConversationChain
+        from langchain_classic.chains import ConversationChain
 
-        _warn_on_import(name, replacement="langchain.chains.ConversationChain")
+        _warn_on_import(name, replacement="langchain_classic.chains.ConversationChain")
 
         return ConversationChain
     if name == "LLMBashChain":
@@ -79,51 +81,53 @@ def __getattr__(name: str) -> Any:
         raise ImportError(msg)
 
     if name == "LLMChain":
-        from langchain.chains import LLMChain
+        from langchain_classic.chains import LLMChain
 
-        _warn_on_import(name, replacement="langchain.chains.LLMChain")
+        _warn_on_import(name, replacement="langchain_classic.chains.LLMChain")
 
         return LLMChain
     if name == "LLMCheckerChain":
-        from langchain.chains import LLMCheckerChain
+        from langchain_classic.chains import LLMCheckerChain
 
-        _warn_on_import(name, replacement="langchain.chains.LLMCheckerChain")
+        _warn_on_import(name, replacement="langchain_classic.chains.LLMCheckerChain")
 
         return LLMCheckerChain
     if name == "LLMMathChain":
-        from langchain.chains import LLMMathChain
+        from langchain_classic.chains import LLMMathChain
 
-        _warn_on_import(name, replacement="langchain.chains.LLMMathChain")
+        _warn_on_import(name, replacement="langchain_classic.chains.LLMMathChain")
 
         return LLMMathChain
     if name == "QAWithSourcesChain":
-        from langchain.chains import QAWithSourcesChain
+        from langchain_classic.chains import QAWithSourcesChain
 
-        _warn_on_import(name, replacement="langchain.chains.QAWithSourcesChain")
+        _warn_on_import(name, replacement="langchain_classic.chains.QAWithSourcesChain")
 
         return QAWithSourcesChain
     if name == "VectorDBQA":
-        from langchain.chains import VectorDBQA
+        from langchain_classic.chains import VectorDBQA
 
-        _warn_on_import(name, replacement="langchain.chains.VectorDBQA")
+        _warn_on_import(name, replacement="langchain_classic.chains.VectorDBQA")
 
         return VectorDBQA
     if name == "VectorDBQAWithSourcesChain":
-        from langchain.chains import VectorDBQAWithSourcesChain
+        from langchain_classic.chains import VectorDBQAWithSourcesChain
 
-        _warn_on_import(name, replacement="langchain.chains.VectorDBQAWithSourcesChain")
+        _warn_on_import(
+            name, replacement="langchain_classic.chains.VectorDBQAWithSourcesChain"
+        )
 
         return VectorDBQAWithSourcesChain
     if name == "InMemoryDocstore":
         from langchain_community.docstore import InMemoryDocstore
 
-        _warn_on_import(name, replacement="langchain.docstore.InMemoryDocstore")
+        _warn_on_import(name, replacement="langchain_classic.docstore.InMemoryDocstore")
 
         return InMemoryDocstore
     if name == "Wikipedia":
         from langchain_community.docstore import Wikipedia
 
-        _warn_on_import(name, replacement="langchain.docstore.Wikipedia")
+        _warn_on_import(name, replacement="langchain_classic.docstore.Wikipedia")
 
         return Wikipedia
     if name == "Anthropic":
@@ -366,39 +370,6 @@ def __getattr__(name: str) -> Any:
         )
 
         return SerpAPIWrapper
-    if name == "verbose":
-        from langchain.globals import _verbose
-
-        _warn_on_import(
-            name,
-            replacement=(
-                "langchain.globals.set_verbose() / langchain.globals.get_verbose()"
-            ),
-        )
-
-        return _verbose
-    if name == "debug":
-        from langchain.globals import _debug
-
-        _warn_on_import(
-            name,
-            replacement=(
-                "langchain.globals.set_debug() / langchain.globals.get_debug()"
-            ),
-        )
-
-        return _debug
-    if name == "llm_cache":
-        from langchain.globals import _llm_cache
-
-        _warn_on_import(
-            name,
-            replacement=(
-                "langchain.globals.set_llm_cache() / langchain.globals.get_llm_cache()"
-            ),
-        )
-
-        return _llm_cache
     msg = f"Could not find: {name}"
     raise AttributeError(msg)
 

libs/langchain/langchain_classic/_api/module_import.py

@@ -3,12 +3,12 @@ from typing import Any, Callable, Optional
 
 from langchain_core._api import internal, warn_deprecated
 
-from langchain._api.interactive_env import is_interactive_env
+from langchain_classic._api.interactive_env import is_interactive_env
 
 ALLOWED_TOP_LEVEL_PKGS = {
     "langchain_community",
     "langchain_core",
-    "langchain",
+    "langchain_classic",
 }
 
 

libs/langchain/langchain_classic/adapters/openai.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.adapters.openai import (

libs/langchain/langchain_classic/agents/__init__.py

@@ -35,8 +35,8 @@ from langchain_core._api.path import as_import_path
 from langchain_core.tools import Tool
 from langchain_core.tools.convert import tool
 
-from langchain._api import create_importer
-from langchain.agents.agent import (
+from langchain_classic._api import create_importer
+from langchain_classic.agents.agent import (
     Agent,
     AgentExecutor,
     AgentOutputParser,
@@ -44,36 +44,38 @@ from langchain.agents.agent import (
     BaseSingleActionAgent,
     LLMSingleActionAgent,
 )
-from langchain.agents.agent_iterator import AgentExecutorIterator
-from langchain.agents.agent_toolkits.vectorstore.base import (
+from langchain_classic.agents.agent_iterator import AgentExecutorIterator
+from langchain_classic.agents.agent_toolkits.vectorstore.base import (
     create_vectorstore_agent,
     create_vectorstore_router_agent,
 )
-from langchain.agents.agent_types import AgentType
-from langchain.agents.conversational.base import ConversationalAgent
-from langchain.agents.conversational_chat.base import ConversationalChatAgent
-from langchain.agents.initialize import initialize_agent
-from langchain.agents.json_chat.base import create_json_chat_agent
-from langchain.agents.loading import load_agent
-from langchain.agents.mrkl.base import MRKLChain, ZeroShotAgent
-from langchain.agents.openai_functions_agent.base import (
+from langchain_classic.agents.agent_types import AgentType
+from langchain_classic.agents.conversational.base import ConversationalAgent
+from langchain_classic.agents.conversational_chat.base import ConversationalChatAgent
+from langchain_classic.agents.initialize import initialize_agent
+from langchain_classic.agents.json_chat.base import create_json_chat_agent
+from langchain_classic.agents.loading import load_agent
+from langchain_classic.agents.mrkl.base import MRKLChain, ZeroShotAgent
+from langchain_classic.agents.openai_functions_agent.base import (
     OpenAIFunctionsAgent,
     create_openai_functions_agent,
 )
-from langchain.agents.openai_functions_multi_agent.base import OpenAIMultiFunctionsAgent
-from langchain.agents.openai_tools.base import create_openai_tools_agent
-from langchain.agents.react.agent import create_react_agent
-from langchain.agents.react.base import ReActChain, ReActTextWorldAgent
-from langchain.agents.self_ask_with_search.base import (
+from langchain_classic.agents.openai_functions_multi_agent.base import (
+    OpenAIMultiFunctionsAgent,
+)
+from langchain_classic.agents.openai_tools.base import create_openai_tools_agent
+from langchain_classic.agents.react.agent import create_react_agent
+from langchain_classic.agents.react.base import ReActChain, ReActTextWorldAgent
+from langchain_classic.agents.self_ask_with_search.base import (
     SelfAskWithSearchChain,
     create_self_ask_with_search_agent,
 )
-from langchain.agents.structured_chat.base import (
+from langchain_classic.agents.structured_chat.base import (
     StructuredChatAgent,
     create_structured_chat_agent,
 )
-from langchain.agents.tool_calling_agent.base import create_tool_calling_agent
-from langchain.agents.xml.base import XMLAgent, create_xml_agent
+from langchain_classic.agents.tool_calling_agent.base import create_tool_calling_agent
+from langchain_classic.agents.xml.base import XMLAgent, create_xml_agent
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.json.base import create_json_agent
@@ -125,7 +127,7 @@ def __getattr__(name: str) -> Any:
             suffix=name,
             relative_to=here,
         )
-        old_path = "langchain." + relative_path
+        old_path = "langchain_classic." + relative_path
         new_path = "langchain_experimental." + relative_path
         msg = (
             f"{name} has been moved to langchain experimental. "

libs/langchain/langchain_classic/agents/agent.py

@@ -44,13 +44,13 @@ from langchain_core.utils.input import get_color_mapping
 from pydantic import BaseModel, ConfigDict, model_validator
 from typing_extensions import Self, override
 
-from langchain._api.deprecation import AGENT_DEPRECATION_WARNING
-from langchain.agents.agent_iterator import AgentExecutorIterator
-from langchain.agents.agent_types import AgentType
-from langchain.agents.tools import InvalidTool
-from langchain.chains.base import Chain
-from langchain.chains.llm import LLMChain
-from langchain.utilities.asyncio import asyncio_timeout
+from langchain_classic._api.deprecation import AGENT_DEPRECATION_WARNING
+from langchain_classic.agents.agent_iterator import AgentExecutorIterator
+from langchain_classic.agents.agent_types import AgentType
+from langchain_classic.agents.tools import InvalidTool
+from langchain_classic.chains.base import Chain
+from langchain_classic.chains.llm import LLMChain
+from langchain_classic.utilities.asyncio import asyncio_timeout
 
 logger = logging.getLogger(__name__)
 

libs/langchain/langchain_classic/agents/agent_iterator.py

@@ -30,11 +30,11 @@ from langchain_core.runnables.utils import AddableDict
 from langchain_core.tools import BaseTool
 from langchain_core.utils.input import get_color_mapping
 
-from langchain.schema import RUN_KEY
-from langchain.utilities.asyncio import asyncio_timeout
+from langchain_classic.schema import RUN_KEY
+from langchain_classic.utilities.asyncio import asyncio_timeout
 
 if TYPE_CHECKING:
-    from langchain.agents.agent import AgentExecutor, NextStepOutput
+    from langchain_classic.agents.agent import AgentExecutor, NextStepOutput
 
 logger = logging.getLogger(__name__)
 

libs/langchain/langchain_classic/agents/agent_toolkits/__init__.py

@@ -20,15 +20,15 @@ from typing import TYPE_CHECKING, Any
 from langchain_core._api.path import as_import_path
 from langchain_core.tools.retriever import create_retriever_tool
 
-from langchain._api import create_importer
-from langchain.agents.agent_toolkits.conversational_retrieval.openai_functions import (
+from langchain_classic._api import create_importer
+from langchain_classic.agents.agent_toolkits.conversational_retrieval.openai_functions import (  # noqa: E501
     create_conversational_retrieval_agent,
 )
-from langchain.agents.agent_toolkits.vectorstore.base import (
+from langchain_classic.agents.agent_toolkits.vectorstore.base import (
     create_vectorstore_agent,
     create_vectorstore_router_agent,
 )
-from langchain.agents.agent_toolkits.vectorstore.toolkit import (
+from langchain_classic.agents.agent_toolkits.vectorstore.toolkit import (
     VectorStoreInfo,
     VectorStoreRouterToolkit,
     VectorStoreToolkit,
@@ -119,7 +119,7 @@ def __getattr__(name: str) -> Any:
     """Get attr name."""
     if name in DEPRECATED_AGENTS:
         relative_path = as_import_path(Path(__file__).parent, suffix=name)
-        old_path = "langchain." + relative_path
+        old_path = "langchain_classic." + relative_path
         new_path = "langchain_experimental." + relative_path
         msg = (
             f"{name} has been moved to langchain experimental. "

libs/langchain/langchain_classic/agents/agent_toolkits/ainetwork/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.ainetwork.toolkit import AINetworkToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/amadeus/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.amadeus.toolkit import AmadeusToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/azure_cognitive_services.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.azure_cognitive_services import (

libs/langchain/langchain_classic/agents/agent_toolkits/clickup/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.clickup.toolkit import ClickupToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/conversational_retrieval/openai_functions.py

@@ -6,12 +6,12 @@ from langchain_core.messages import SystemMessage
 from langchain_core.prompts.chat import MessagesPlaceholder
 from langchain_core.tools import BaseTool
 
-from langchain.agents.agent import AgentExecutor
-from langchain.agents.openai_functions_agent.agent_token_buffer_memory import (
+from langchain_classic.agents.agent import AgentExecutor
+from langchain_classic.agents.openai_functions_agent.agent_token_buffer_memory import (
     AgentTokenBufferMemory,
 )
-from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
-from langchain.memory.token_buffer import ConversationTokenBufferMemory
+from langchain_classic.agents.openai_functions_agent.base import OpenAIFunctionsAgent
+from langchain_classic.memory.token_buffer import ConversationTokenBufferMemory
 
 
 def _get_default_system_message() -> SystemMessage:

libs/langchain/langchain_classic/agents/agent_toolkits/conversational_retrieval/tool.py

@@ -0,0 +1,3 @@
+from langchain_classic.tools.retriever import create_retriever_tool
+
+__all__ = ["create_retriever_tool"]

libs/langchain/langchain_classic/agents/agent_toolkits/csv/__init__.py

@@ -12,7 +12,7 @@ def __getattr__(name: str) -> Any:
             "and https://github.com/langchain-ai/langchain/discussions/11680"
             "To keep using this code as is, install langchain experimental and "
             "update your import statement from:\n "
-            f"`langchain.agents.agent_toolkits.csv.{name}` to "
+            f"`langchain_classic.agents.agent_toolkits.csv.{name}` to "
             f"`langchain_experimental.agents.agent_toolkits.{name}`."
         )
         raise ImportError(msg)

libs/langchain/langchain_classic/agents/agent_toolkits/file_management/__init__.py

@@ -2,7 +2,7 @@
 
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.file_management.toolkit import (

libs/langchain/langchain_classic/agents/agent_toolkits/file_management/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.file_management.toolkit import (

libs/langchain/langchain_classic/agents/agent_toolkits/github/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.github.toolkit import (

libs/langchain/langchain_classic/agents/agent_toolkits/gitlab/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.gitlab.toolkit import GitLabToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/gmail/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.gmail.toolkit import GmailToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/jira/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.jira.toolkit import JiraToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/json/base.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.json.base import create_json_agent

libs/langchain/langchain_classic/agents/agent_toolkits/json/prompt.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.json.prompt import JSON_PREFIX, JSON_SUFFIX

libs/langchain/langchain_classic/agents/agent_toolkits/json/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.json.toolkit import JsonToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/multion/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.multion.toolkit import MultionToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/nasa/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.nasa.toolkit import NasaToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/nla/tool.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.nla.tool import NLATool

libs/langchain/langchain_classic/agents/agent_toolkits/nla/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.nla.toolkit import NLAToolkit

libs/langchain/langchain_classic/agents/agent_toolkits/office365/toolkit.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.office365.toolkit import O365Toolkit

libs/langchain/langchain_classic/agents/agent_toolkits/openapi/base.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.openapi.base import create_openapi_agent

libs/langchain/langchain_classic/agents/agent_toolkits/openapi/planner.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.openapi.planner import (

libs/langchain/langchain_classic/agents/agent_toolkits/openapi/planner_prompt.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.openapi.planner_prompt import (

libs/langchain/langchain_classic/agents/agent_toolkits/openapi/prompt.py

@@ -1,6 +1,6 @@
 from typing import TYPE_CHECKING, Any
 
-from langchain._api import create_importer
+from langchain_classic._api import create_importer
 
 if TYPE_CHECKING:
     from langchain_community.agent_toolkits.openapi.prompt import (