25 Commits (f8a54d1d731a816897d3b4b0a0f814a099231580)

Author	SHA1	Message	Date
Kirushikesh DB	12861273e1	experimental[patch]: Removed 'SQLResults:' from the LLMResponse in SQLDatabaseChain (#17104) ... **Description:** When using the SQLDatabaseChain with Llama2-70b LLM and, SQLite database. I was getting `Warning: You can only execute one statement at a time.`. ``` from langchain.sql_database import SQLDatabase from langchain_experimental.sql import SQLDatabaseChain sql_database_path = '/dccstor/mmdataretrieval/mm_dataset/swimming_record/rag_data/swimmingdataset.db' sql_db = get_database(sql_database_path) db_chain = SQLDatabaseChain.from_llm(mistral, sql_db, verbose=True, callbacks = [callback_obj]) db_chain.invoke({ "query": "What is the best time of Lance Larson in men's 100 meter butterfly competition?" }) ``` Error: ``` Warning Traceback (most recent call last) Cell In[31], line 3 1 import langchain 2 langchain.debug=False ----> 3 db_chain.invoke({ 4 "query": "What is the best time of Lance Larson in men's 100 meter butterfly competition?" 5 }) File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/langchain/chains/base.py:162, in Chain.invoke(self, input, config, **kwargs) 160 except BaseException as e: 161 run_manager.on_chain_error(e) --> 162 raise e 163 run_manager.on_chain_end(outputs) 164 final_outputs: Dict[str, Any] = self.prep_outputs( 165 inputs, outputs, return_only_outputs 166 ) File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/langchain/chains/base.py:156, in Chain.invoke(self, input, config, **kwargs) 149 run_manager = callback_manager.on_chain_start( 150 dumpd(self), 151 inputs, 152 name=run_name, 153 ) 154 try: 155 outputs = ( --> 156 self._call(inputs, run_manager=run_manager) 157 if new_arg_supported 158 else self._call(inputs) 159 ) 160 except BaseException as e: 161 run_manager.on_chain_error(e) File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/langchain_experimental/sql/base.py:198, in SQLDatabaseChain._call(self, inputs, run_manager) 194 except Exception as exc: 195 # Append intermediate steps to exception, to aid in logging and later 196 # improvement of few shot prompt seeds 197 exc.intermediate_steps = intermediate_steps # type: ignore --> 198 raise exc File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/langchain_experimental/sql/base.py:143, in SQLDatabaseChain._call(self, inputs, run_manager) 139 intermediate_steps.append( 140 sql_cmd 141 ) # output: sql generation (no checker) 142 intermediate_steps.append({"sql_cmd": sql_cmd}) # input: sql exec --> 143 result = self.database.run(sql_cmd) 144 intermediate_steps.append(str(result)) # output: sql exec 145 else: File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/langchain_community/utilities/sql_database.py:436, in SQLDatabase.run(self, command, fetch, include_columns) 425 def run( 426 self, 427 command: str, 428 fetch: Literal["all", "one"] = "all", 429 include_columns: bool = False, 430 ) -> str: 431 """Execute a SQL command and return a string representing the results. 432 433 If the statement returns rows, a string of the results is returned. 434 If the statement returns no rows, an empty string is returned. 435 """ --> 436 result = self._execute(command, fetch) 438 res = [ 439 { 440 column: truncate_word(value, length=self._max_string_length) (...) 443 for r in result 444 ] 446 if not include_columns: File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/langchain_community/utilities/sql_database.py:413, in SQLDatabase._execute(self, command, fetch) 410 elif self.dialect == "postgresql": # postgresql 411 connection.exec_driver_sql("SET search_path TO %s", (self._schema,)) --> 413 cursor = connection.execute(text(command)) 414 if cursor.returns_rows: 415 if fetch == "all": File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/sqlalchemy/engine/base.py:1416, in Connection.execute(self, statement, parameters, execution_options) 1414 raise exc.ObjectNotExecutableError(statement) from err 1415 else: -> 1416 return meth( 1417 self, 1418 distilled_parameters, 1419 execution_options or NO_OPTIONS, 1420 ) File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/sqlalchemy/sql/elements.py:516, in ClauseElement._execute_on_connection(self, connection, distilled_params, execution_options) 514 if TYPE_CHECKING: 515 assert isinstance(self, Executable) --> 516 return connection._execute_clauseelement( 517 self, distilled_params, execution_options 518 ) 519 else: 520 raise exc.ObjectNotExecutableError(self) File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/sqlalchemy/engine/base.py:1639, in Connection._execute_clauseelement(self, elem, distilled_parameters, execution_options) 1627 compiled_cache: Optional[CompiledCacheType] = execution_options.get( 1628 "compiled_cache", self.engine._compiled_cache 1629 ) 1631 compiled_sql, extracted_params, cache_hit = elem._compile_w_cache( 1632 dialect=dialect, 1633 compiled_cache=compiled_cache, (...) 1637 linting=self.dialect.compiler_linting | compiler.WARN_LINTING, 1638 ) -> 1639 ret = self._execute_context( 1640 dialect, 1641 dialect.execution_ctx_cls._init_compiled, 1642 compiled_sql, 1643 distilled_parameters, 1644 execution_options, 1645 compiled_sql, 1646 distilled_parameters, 1647 elem, 1648 extracted_params, 1649 cache_hit=cache_hit, 1650 ) 1651 if has_events: 1652 self.dispatch.after_execute( 1653 self, 1654 elem, (...) 1658 ret, 1659 ) File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/sqlalchemy/engine/base.py:1848, in Connection._execute_context(self, dialect, constructor, statement, parameters, execution_options, *args, **kw) 1843 return self._exec_insertmany_context( 1844 dialect, 1845 context, 1846 ) 1847 else: -> 1848 return self._exec_single_context( 1849 dialect, context, statement, parameters 1850 ) File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/sqlalchemy/engine/base.py:1988, in Connection._exec_single_context(self, dialect, context, statement, parameters) 1985 result = context._setup_result_proxy() 1987 except BaseException as e: -> 1988 self._handle_dbapi_exception( 1989 e, str_statement, effective_parameters, cursor, context 1990 ) 1992 return result File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/sqlalchemy/engine/base.py:2346, in Connection._handle_dbapi_exception(self, e, statement, parameters, cursor, context, is_sub_exec) 2344 else: 2345 assert exc_info[1] is not None -> 2346 raise exc_info[1].with_traceback(exc_info[2]) 2347 finally: 2348 del self._reentrant_error File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/sqlalchemy/engine/base.py:1969, in Connection._exec_single_context(self, dialect, context, statement, parameters) 1967 break 1968 if not evt_handled: -> 1969 self.dialect.do_execute( 1970 cursor, str_statement, effective_parameters, context 1971 ) 1973 if self._has_events or self.engine._has_events: 1974 self.dispatch.after_cursor_execute( 1975 self, 1976 cursor, (...) 1980 context.executemany, 1981 ) File ~/.conda/envs/guardrails1/lib/python3.9/site-packages/sqlalchemy/engine/default.py:922, in DefaultDialect.do_execute(self, cursor, statement, parameters, context) 921 def do_execute(self, cursor, statement, parameters, context=None): --> 922 cursor.execute(statement, parameters) Warning: You can only execute one statement at a time. ``` **Issue:** The Error occurs because when generating the SQLQuery, the llm_input includes the stop character of "\nSQLResult:", so for this user query the LLM generated response is **SELECT Time FROM men_butterfly_100m WHERE Swimmer = 'Lance Larson';\nSQLResult:** it is required to remove the SQLResult suffix on the llm response before executing it on the database. ``` llm_inputs = { "input": input_text, "top_k": str(self.top_k), "dialect": self.database.dialect, "table_info": table_info, "stop": ["\nSQLResult:"], } sql_cmd = self.llm_chain.predict( callbacks=_run_manager.get_child(), **llm_inputs, ).strip() if SQL_RESULT in sql_cmd: sql_cmd = sql_cmd.split(SQL_RESULT)[0].strip() result = self.database.run(sql_cmd) ``` <!-- Thank you for contributing to LangChain! Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified. Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes if applicable, - **Dependencies:** any dependencies required for this change, - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` from the root of the package you've modified to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Leonid Ganeline	4159a4723c	experimental[patch]: update module doc strings (#19539) ... Added missed module descriptions. Fixed format.	6 months ago
Leonid Ganeline	3f6bf852ea	experimental: docstrings update (#18048) ... Added missed docstrings. Formatted docsctrings to the consistent format.	7 months ago
Erick Friis	ed789be8f4	docs, templates: update schema imports to core (#17885) ... - chat models, messages - documents - agentaction/finish - baseretriever,document - stroutputparser - more messages - basemessage - format_document - baseoutputparser --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	7 months ago
Eugene Yurtsev	780e84ae79	community[minor]: SQLDatabase Add fetch mode `cursor`, query parameters, query by selectable, expose execution options, and documentation (#17191) ... - **Description:** Improve `SQLDatabase` adapter component to promote code re-use, see [suggestion](https://github.com/langchain-ai/langchain/pull/16246#pullrequestreview-1846590962). - **Needed by:** GH-16246 - **Addressed to:** @baskaryan, @cbornet ## Details - Add `cursor` fetch mode - Accept SQL query parameters - Accept both `str` and SQLAlchemy selectables as query expression - Expose `execution_options` - Documentation page (notebook) about `SQLDatabase` [^1] See [About SQLDatabase](https://github.com/langchain-ai/langchain/blob/c1c7b763/docs/docs/integrations/tools/sql_database.ipynb). [^1]: Apparently there hasn't been any yet? --------- Co-authored-by: Andreas Motl <andreas.motl@crate.io>	7 months ago
Bagatur	baeac236b6	langchain[patch], experimental[patch]: update utilities imports (#15438)	9 months ago
Bagatur	1678d6ca17	langchain[patch], experimental[patch], docs: update tools imports (#15433)	9 months ago
Bagatur	480626dc99	docs, community[patch], experimental[patch], langchain[patch], cli[pa… (#15412) ... …tch]: import models from community ran ```bash git grep -l 'from langchain\.chat_models' | xargs -L 1 sed -i '' "s/from\ langchain\.chat_models/from\ langchain_community.chat_models/g" git grep -l 'from langchain\.llms' | xargs -L 1 sed -i '' "s/from\ langchain\.llms/from\ langchain_community.llms/g" git grep -l 'from langchain\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.embeddings/from\ langchain_community.embeddings/g" git checkout master libs/langchain/tests/unit_tests/llms git checkout master libs/langchain/tests/unit_tests/chat_models git checkout master libs/langchain/tests/unit_tests/embeddings/test_imports.py make format cd libs/langchain; make format cd ../experimental; make format cd ../core; make format ```	9 months ago
Bagatur	8e0d5813c2	langchain[patch], experimental[patch]: replace langchain.schema imports (#15410) ... Import from core instead. Ran: ```bash git grep -l 'from langchain.schema\.output_parser' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.output_parser/from\ langchain_core.output_parsers/g" git grep -l 'from langchain.schema\.messages' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.messages/from\ langchain_core.messages/g" git grep -l 'from langchain.schema\.document' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.document/from\ langchain_core.documents/g" git grep -l 'from langchain.schema\.runnable' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.runnable/from\ langchain_core.runnables/g" git grep -l 'from langchain.schema\.vectorstore' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.vectorstore/from\ langchain_core.vectorstores/g" git grep -l 'from langchain.schema\.language_model' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.language_model/from\ langchain_core.language_models/g" git grep -l 'from langchain.schema\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.embeddings/from\ langchain_core.embeddings/g" git grep -l 'from langchain.schema\.storage' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.storage/from\ langchain_core.stores/g" git checkout master libs/langchain/tests/unit_tests/schema/ make format cd libs/experimental make format cd ../langchain make format ```	9 months ago
Abdul	82102c99b3	langchain[patch]: Running SQLDatabaseChain adds prefix "SQLQuery:\n" (#14058) ... - **Issue:** https://github.com/langchain-ai/langchain/issues/12077 --------- Co-authored-by: Abdul Kader Maliyakkal <maliyakk@amazon.com>	10 months ago
Qihui Xie	57ade13b2b	fix llm_inputs duplication problem in intermediate_steps in SQLDatabaseChain (#10279) ... Use `.copy()` to fix the bug that the first `llm_inputs` element is overwritten by the second `llm_inputs` element in `intermediate_steps`. ***Problem description:*** In [line 127]( c732d8fffd/libs/experimental/langchain_experimental/sql/base.py (L127C17-L127C17)), the `llm_inputs` of the sql generation step is appended as the first element of `intermediate_steps`: ``` intermediate_steps.append(llm_inputs) # input: sql generation ``` However, `llm_inputs` is a mutable dict, it is updated in [line 179](https://github.com/langchain-ai/langchain/blob/master/libs/experimental/langchain_experimental/sql/base.py#L179) for the final answer step: ``` llm_inputs["input"] = input_text ``` Then, the updated `llm_inputs` is appended as another element of `intermediate_steps` in [line 180](c732d8fffd/libs/experimental/langchain_experimental/sql/base.py (L180)): ``` intermediate_steps.append(llm_inputs) # input: final answer ``` As a result, the final `intermediate_steps` returned in [line 189](c732d8fffd/libs/experimental/langchain_experimental/sql/base.py (L189C43-L189C43)) actually contains two same `llm_inputs` elements, i.e., the `llm_inputs` for the sql generation step overwritten by the one for final answer step by mistake. Users are not able to get the actual `llm_inputs` for the sql generation step from `intermediate_steps` Simply calling `.copy()` when appending `llm_inputs` to `intermediate_steps` can solve this problem.	12 months ago
Predrag Gruevski	c9986bc3a9	Tweak type hints to match dependency's behavior. (#11355) ... Needs #11353 to merge first, and a new `langchain` to be published with those changes.	12 months ago
Mohammad Mohtashim	3bddd708f7	Add memory to sql chain (#8597) ... continuation of PR #8550 @hwchase17 please see and merge. And also close the PR #8550. --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>	12 months ago
Nuno Campos	7b13292e35	Remove python eval from vector sql db chain (#10937) ... <!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->	1 year ago
Aashish Saini	1b050b98f5	Corrected some spelling mistakes and grammatical errors (#10791) ... Corrected some spelling mistakes and grammatical errors CC: @baskaryan, @eyurtsev, @hwchase17. --------- Co-authored-by: Ishita Chauhan <136303787+IshitaChauhanShortHillsAI@users.noreply.github.com> Co-authored-by: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com> Co-authored-by: ManpreetShorthillsAI <142380984+ManpreetShorthillsAI@users.noreply.github.com> Co-authored-by: AryamanJaiswalShorthillsAI <142397527+AryamanJaiswalShorthillsAI@users.noreply.github.com> Co-authored-by: Adarsh Shrivastav <142413097+AdarshKumarShorthillsAI@users.noreply.github.com> Co-authored-by: Vishal <141389263+VishalYadavShorthillsAI@users.noreply.github.com> Co-authored-by: ChetnaGuptaShorthillsAI <142381084+ChetnaGuptaShorthillsAI@users.noreply.github.com> Co-authored-by: PankajKumarShorthillsAI <142473460+PankajKumarShorthillsAI@users.noreply.github.com> Co-authored-by: AbhishekYadavShorthillsAI <142393903+AbhishekYadavShorthillsAI@users.noreply.github.com> Co-authored-by: AmitSinghShorthillsAI <142410046+AmitSinghShorthillsAI@users.noreply.github.com> Co-authored-by: Md Nazish Arman <142379599+MdNazishArmanShorthillsAI@users.noreply.github.com> Co-authored-by: KamalSharmaShorthillsAI <142474019+KamalSharmaShorthillsAI@users.noreply.github.com> Co-authored-by: Lakshya <lakshyagupta87@yahoo.com> Co-authored-by: Aayush <142384656+AayushShorthillsAI@users.noreply.github.com> Co-authored-by: AnujMauryaShorthillsAI <142393269+AnujMauryaShorthillsAI@users.noreply.github.com> Co-authored-by: ishita <chauhanishita5356@gmail.com>	1 year ago
Harrison Chase	12ff780089	move embeddings to schema (#10696)	1 year ago
Harrison Chase	5442d2b1fa	Harrison/stop importing from init (#10690)	1 year ago
Hedeer El Showk	9749f8ebae	database -> db in from_llm (#10667) ... **Description:** Renamed argument `database` in `SQLDatabaseSequentialChain.from_llm()` to `db`, I realize it's tiny and a bit of a nitpick but for consistency with SQLDatabaseChain (and all the others actually) I thought it should be renamed. Also got me while working and using it today. ✔️ Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally.	1 year ago
刘 方瑞	890ed775a3	Resolve: VectorSearch enabled SQLChain? (#10177) ... Squashed from #7454 with updated features We have separated the `SQLDatabseChain` from `VectorSQLDatabseChain` and put everything into `experimental/`. Below is the original PR message from #7454. ------- We have been working on features to fill up the gap among SQL, vector search and LLM applications. Some inspiring works like self-query retrievers for VectorStores (for example [Weaviate](https://python.langchain.com/en/latest/modules/indexes/retrievers/examples/weaviate_self_query.html) and [others](https://python.langchain.com/en/latest/modules/indexes/retrievers/examples/self_query.html)) really turn those vector search databases into a powerful knowledge base! 🚀🚀 We are thinking if we can merge all in one, like SQL and vector search and LLMChains, making this SQL vector database memory as the only source of your data. Here are some benefits we can think of for now, maybe you have more 👀: With ALL data you have: since you store all your pasta in the database, you don't need to worry about the foreign keys or links between names from other data source. Flexible data structure: Even if you have changed your schema, for example added a table, the LLM will know how to JOIN those tables and use those as filters. SQL compatibility: We found that vector databases that supports SQL in the marketplace have similar interfaces, which means you can change your backend with no pain, just change the name of the distance function in your DB solution and you are ready to go! ### Issue resolved: - [Feature Proposal: VectorSearch enabled SQLChain?](https://github.com/hwchase17/langchain/issues/5122) ### Change made in this PR: - An improved schema handling that ignore `types.NullType` columns - A SQL output Parser interface in `SQLDatabaseChain` to enable Vector SQL capability and further more - A Retriever based on `SQLDatabaseChain` to retrieve data from the database for RetrievalQAChains and many others - Allow `SQLDatabaseChain` to retrieve data in python native format - Includes PR #6737 - Vector SQL Output Parser for `SQLDatabaseChain` and `SQLDatabaseChainRetriever` - Prompts that can implement text to VectorSQL - Corresponding unit-tests and notebook ### Twitter handle: - @MyScaleDB ### Tag Maintainer: Prompts / General: @hwchase17, @baskaryan DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev ### Dependencies: No dependency added	1 year ago
Programmers Emperor	872d829201	Update __init__.py (#9955) ... Add SQLDatabaseSequentialChain Class to __init__.py so it can be accessed and used <!-- Thank you for contributing to LangChain! Replace this entire comment with: - Description: SQLDatabaseSequentialChain is not found when importing Langchain_experimental package, when I open __init__.py Langchain_expermental.sql, I found that SQLDatabaseSequentialChain is imported and add to __all__ list - Issue: SQLDatabaseSequentialChain is not found in Langchain_experimental package - Dependencies: None, - Tag maintainer: None, - Twitter handle: None, Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. These live is docs/extras directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17, @rlancemartin. -->	1 year ago
Predrag Gruevski	eb3d1fa93c	Add security warning to experimental `SQLDatabaseChain` class. (#9867) ... The most reliable way to not have a chain run an undesirable SQL command is to not give it database permissions to run that command. That way the database itself performs the rule enforcement, so it's much easier to configure and use properly than anything we could add in ourselves.	1 year ago
Nuno Campos	c0d67420e5	Use a submodule for pydantic v1 compat (#9371) ... <!-- Thank you for contributing to LangChain! Replace this entire comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - Twitter handle: we announce bigger features on Twitter. If your PR gets announced and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. These live is docs/extras directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17, @rlancemartin. -->	1 year ago
Eugene Yurtsev	2673b3a314	Create pydantic v1 namespace in langchain (#9254) ... Create pydantic v1 namespace in langchain experimental	1 year ago
Harrison Chase	1b0bfa54cf	cr	1 year ago
Harrison Chase	aa0e69bc98	Harrison/official pre release (#8106)	1 year ago