langchain

Commit Graph

Author	SHA1	Message	Date
Brace Sproul	abe7566d7d	core[minor]: BaseChatModel with_structured_output implementation (#22859 )	3 months ago
Raviraj	858ce264ef	SemanticChunker : Feature Addition ("Semantic Splitting with gradient") (#22895 ) ```SemanticChunker``` currently provide three methods to split the texts semantically: - percentile - standard_deviation - interquartile I propose new method ```gradient```. In this method, the gradient of distance is used to split chunks along with the percentile method (technically) . This method is useful when chunks are highly correlated with each other or specific to a domain e.g. legal or medical. The idea is to apply anomaly detection on gradient array so that the distribution become wider and easy to identify boundaries in highly semantic data. I have tested this merge on a set of 10 domain specific documents (mostly legal). Details : - Issue: Improvement - Dependencies: NA - Twitter handle: [x.com/prajapat_ravi](https://x.com/prajapat_ravi) @hwchase17 --------- Co-authored-by: Raviraj Prajapat <raviraj.prajapat@sirionlabs.com> Co-authored-by: isaac hershenson <ihershenson@hmc.edu>	3 months ago
Tomaz Bratanic	1c661fd849	Improve llm graph transformer docstring (#22939 )	3 months ago
Erick Friis	c374c98389	experimental: release 0.0.61 (#22924 )	3 months ago
Istvan/Nebulinq	513e491ce9	experimental: LLMGraphTransformer - added relationship properties. (#21856 ) - Description: The generated relationships in the graph had no properties, but the Relationship class was properly defined with properties. This made it very difficult to transform conditional sentences into a graph. Adding properties to relationships can solve this issue elegantly. The changes expand on the existing LLMGraphTransformer implementation but add the possibility to define allowed relationship properties like this: LLMGraphTransformer(llm=llm, relationship_properties=["Condition", "Time"],) - Issue: no issue found - Dependencies: n/a - Twitter handle: @IstvanSpace -Quick Test ================================================================= from dotenv import load_dotenv import os from langchain_community.graphs import Neo4jGraph from langchain_experimental.graph_transformers import LLMGraphTransformer from langchain_openai import ChatOpenAI from langchain_core.prompts import ChatPromptTemplate from langchain_core.documents import Document load_dotenv() os.environ["NEO4J_URI"] = os.getenv("NEO4J_URI") os.environ["NEO4J_USERNAME"] = os.getenv("NEO4J_USERNAME") os.environ["NEO4J_PASSWORD"] = os.getenv("NEO4J_PASSWORD") graph = Neo4jGraph() llm = ChatOpenAI(temperature=0, model_name="gpt-4o") llm_transformer = LLMGraphTransformer(llm=llm) #text = "Harry potter likes pies, but only if it rains outside" text = "Jack has a dog named Max. Jack only walks Max if it is sunny outside." documents = [Document(page_content=text)] llm_transformer_props = LLMGraphTransformer( llm=llm, relationship_properties=["Condition"], ) graph_documents_props = llm_transformer_props.convert_to_graph_documents(documents) print(f"Nodes:{graph_documents_props[0].nodes}") print(f"Relationships:{graph_documents_props[0].relationships}") graph.add_graph_documents(graph_documents_props) --------- Co-authored-by: Istvan Lorincz <istvan.lorincz@pm.me> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	3 months ago
Eugene Yurtsev	c72bcda4f2	community[major], experimental[patch]: Remove Python REPL from community (#22904 ) Remove the REPL from community, and suggest an alternative import from langchain_experimental. Fix for this issue: https://github.com/langchain-ai/langchain/issues/14345 This is not a bug in the code or an actual security risk. The python REPL itself is behaving as expected. The PR is done to appease blanket security policies that are just looking for the presence of exec in the code. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	3 months ago
Kagura Chen	57783c5e55	Fix: lint errors and update Field alias in models.py and AutoSelectionScorer initialization (#22846 ) This PR addresses several lint errors in the core package of LangChain. Specifically, the following issues were fixed: 1.Unexpected keyword argument "required" for "Field" [call-arg] 2.tests/integration_tests/chains/test_cpal.py:263: error: Unexpected keyword argument "narrative_input" for "QueryModel" [call-arg]	3 months ago
Eugene Yurtsev	a766815a99	experimental[patch]/docs[patch]: Update links to security docs (#22864 ) Minor update to newest version of security docs (content should be identical).	3 months ago
Eugene Yurtsev	ce0b0f22a1	experimental[major]: Force users to opt-in into code that relies on the python repl (#22860 ) This should make it obvious that a few of the agents in langchain experimental rely on the python REPL as a tool under the hood, and will force users to opt-in.	3 months ago
Karim Lalani	276be6cdd4	[experimental][llms][OllamaFunctions] tool calling related fixes (#22339 ) Fixes issues with tool calling to handle tool objects correctly. Added support to handle ToolMessage correctly. Added additional checks for error conditions. --------- Co-authored-by: ccurme <chester.curme@gmail.com>	3 months ago
Christophe Bornet	d04e899b56	ci: add testing with Python 3.12 (#22813 ) We need to use a different version of numpy for py3.8 and py3.12 in pyproject. And so do projects that use that Python version range and import langchain. - Twitter handle: _cbornet	3 months ago
Erick Friis	a24a9c6427	multiple: get rid of pyproject extras (#22581 ) They cause `poetry lock` to take a ton of time, and `uv pip install` can resolve the constraints from these toml files in trivial time (addressing problem with #19153) This allows us to properly upgrade lockfile dependencies moving forward, which revealed some issues that were either fixed or type-ignored (see file comments)	3 months ago
Mohammad Mohtashim	7fcef2556c	[Experimental]: Async agenerate method ollama functions (#21682 ) - Description: : Added Async method for Generate for OllamaFunctions which was missing and was raising errors for the users. - Issue: #21422	3 months ago
Bagatur	48fba40fce	experimental[patch]: Release 0.0.60 (#22497 )	3 months ago
liugz18	8fd231086e	experimental[patch]: Fix graph_transformers llms #21482 (#22417 ) Fix AttributeError on calling LLMGraphTransformer.convert_to_graph_documents #21482 since raw_schema is always a str @baskaryan	3 months ago
Karim Lalani	a1899439fc	[experimental][llms][ollama_functions] Update OllamaFunctions to send `tool_calls` attribute (#21625 ) Update OllamaFunctions to return `tool_calls` for AIMessages when used for tool calling.	4 months ago
Bagatur	50186da0a1	infra: rm unused # noqa violations (#22049 ) Updating #21137	4 months ago
mochi	63284ffebf	experimental[patch], docs: refine notebook for MyScale `SelfQueryRetriever` (#22016 ) - Description: upgrade model to `gpt-4o`	4 months ago
Tomaz Bratanic	a43515ca65	experimental[patch]: Pass enum only to openai in llm graph transformer (#21860 ) Some models like Groq return bad request if you pass in `enum` parameter in tool definition	4 months ago
Erick Friis	2d3f4e1a16	experimental: release 0.0.59 (#21835 )	4 months ago
Erick Friis	c77d2f2b06	multiple: core 0.2 nonbreaking dep, check_diff community->langchain dep (#21646 ) 0.2 is not a breaking release for core (but it is for langchain and community) To keep the core+langchain+community packages in sync at 0.2, we will relax deps throughout the ecosystem to tolerate `langchain-core` 0.2	4 months ago
Tomaz Bratanic	89ff6a3d3b	Add sentiment and confidence levels to diffbotgraphtransformer (#21590 ) Co-authored-by: Erick Friis <erickfriis@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>	4 months ago
Erick Friis	83eecd54fe	experimental: 0.2 relax (#21468 )	4 months ago
Eugene Yurtsev	f92006de3c	multiple: langchain 0.2 in master (#21191 ) 0.2rc migrations - [x] Move memory - [x] Move remaining retrievers - [x] graph_qa chains - [x] some dependency from evaluation code potentially on math utils - [x] Move openapi chain from `langchain.chains.api.openapi` to `langchain_community.chains.openapi` - [x] Migrate `langchain.chains.ernie_functions` to `langchain_community.chains.ernie_functions` - [x] migrate `langchain/chains/llm_requests.py` to `langchain_community.chains.llm_requests` - [x] Moving `langchain_community.cross_enoders.base:BaseCrossEncoder` -> `langchain_community.retrievers.document_compressors.cross_encoder:BaseCrossEncoder` (namespace not ideal, but it needs to be moved to `langchain` to avoid circular deps) - [x] unit tests langchain -- add pytest.mark.community to some unit tests that will stay in langchain - [x] unit tests community -- move unit tests that depend on community to community - [x] mv integration tests that depend on community to community - [x] mypy checks Other todo - [x] Make deprecation warnings not noisy (need to use warn deprecated and check that things are implemented properly) - [x] Update deprecation messages with timeline for code removal (likely we actually won't be removing things until 0.4 release) -- will give people more time to transition their code. - [ ] Add information to deprecation warning to show users how to migrate their code base using langchain-cli - [ ] Remove any unnecessary requirements in langchain (e.g., is SQLALchemy required?) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	4 months ago
Erick Friis	bbdf0f8801	experimental[patch]: core and langchain dep (#21402 )	4 months ago
Erick Friis	e4aca0d052	experimental[patch]: release 0.0.58 (#21397 )	4 months ago
Tomaz Bratanic	0bf7596839	Add simple node properties to llm graph transformer (#21369 ) Add support for simple node properties in llm graph transformer. Linter and dynamic pydantic classes aren't friends, hence I added two ignores	4 months ago
Tomaz Bratanic	ad3fd44a7f	experimental: Fix llm graph transformer bug (#21362 )	4 months ago
Tomaz Bratanic	5b6d1a907d	Add the extract types to diffbot graph transformer (#21315 ) Before you could only extract triples (diffbot calls it facts) from diffbot to avoid isolated nodes. However, sometimes isolated nodes can still be useful like for prefiltering, so we want to allow users to extract them if they want. Default behaviour is unchanged.	4 months ago
ccurme	6da3d92b42	(all): update removal in deprecation warnings from 0.2 to 0.3 (#21265 ) We are pushing out the removal of these to 0.3. `find . -type f -name "*.py" -exec sed -i '' 's/removal="0\.2/removal="0.3/g' {} +`	4 months ago
Liu Xiaodong	3b473d10f2	experimental: clean python repl input（experimental：Added code for PythonREPL） (#20930 ) Update python.py（experimental：Added code for PythonREPL） Added code for PythonREPL, defining a static method 'sanitize_input' that takes the string 'query' as input and returns a sanitizing string. The purpose of this method is to remove unwanted characters from the input string, Specifically: 1. Delete the whitespace at the beginning and end of the string (' \s'). 2. Remove the quotation marks (`` ` ``) at the beginning and end of the string. 3. Remove the keyword "python" at the beginning of the string (case insensitive) because the user may have typed it. This method uses regular expressions (regex) to implement sanitizing. It all started with this code： from langchain.agents import Tool from langchain_experimental.utilities import PythonREPL python_repl = PythonREPL() repl_tool = Tool( name="python_repl", description="Remove redundant formatting marks at the beginning and end of source code from input.Use a Python shell to execute python commands. If you want to see the output of a value, you should print it out with `print(...)`.", func=python_repl.run, ) When I call the agent to write a piece of code for me and execute it with the defined code, I must get an error: SyntaxError('invalid syntax', ('<string>', 1, 1,'In', 1, 2)) After checking, I found that pythonREPL has less formatting of input code than the soon-to-be deprecated pythonREPL tool, so I added this step to it, so that no matter what code I ask the agent to write for me, it can be executed smoothly and get the output result. I have tried modifying the prompt words to solve this problem before, but it did not work, and by adding a simple format check, the problem is well resolved. <img width="1271" alt="image" src="https://github.com/langchain-ai/langchain/assets/164149097/c49a685f-d246-4b11-b655-fd952fc2f04c"> --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Tomaz Bratanic	7860e4c649	experimental[patch]: Add support for non-function calling LLMs in llm graph transformers (#21014 )	5 months ago
Karim Lalani	2ddac9a7c3	experimental[minor]: Add bind_tools and with_structured_output functions to OllamaFunctions (#20881 ) Implemented bind_tools for OllamaFunctions. Made OllamaFunctions sub class of ChatOllama. Implemented with_structured_output for OllamaFunctions. integration unit test has been updated. notebook has been updated. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Michael Schock	5e60d65917	experimental[patch]: return from HuggingGPT task executor task.run() exception (#20219 ) Description: Fixes a bug in the HuggingGPT task execution logic here: except Exception as e: self.status = "failed" self.message = str(e) self.status = "completed" self.save_product() where a caught exception effectively just sets `self.message` and can then throw an exception if, e.g., `self.product` is not defined. Issue: None that I'm aware of. Dependencies: None Twitter handle: https://twitter.com/michaeljschock Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	5 months ago
Michael Schock	63a07f52df	experimental[patch]: remove \n from AutoGPT feedback_tool exit check (#20132 )	5 months ago
GustavoSept	c2d09a5186	experimental[patch]: Makes regex customizable in text_splitter.py (SemanticChunker class) (#20485 ) - Description: Currently, the regex is static (`r"(?<=[.?!])\s+"`), which is only useful for certain use cases. The current change only moves this to be a parameter of split_text(). Which adds flexibility without making it more complex (as the default regex is still the same). - Issue: Not applicable (I searched, no one seems to have created this issue yet). - Dependencies: None. _If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17._ --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Oleksandr Yaremchuk	9428923bab	experimental[minor]: upgrade the prompt injection model (#20783 ) - Description: In January, Laiyer.ai became part of ProtectAI, which means the model became owned by ProtectAI. In addition to that, yesterday, we released a new version of the model addressing issues the Langchain's community and others mentioned to us about false-positives. The new model has a better accuracy compared to the previous version, and we thought the Langchain community would benefit from using the [latest version of the model](https://huggingface.co/protectai/deberta-v3-base-prompt-injection-v2). - Issue: N/A - Dependencies: N/A - Twitter handle: @alex_yaremchuk	5 months ago
ccurme	c010ec8b71	patch: deprecate (a)get_relevant_documents (#20477 ) - `.get_relevant_documents(query)` -> `.invoke(query)` - `.get_relevant_documents(query=query)` -> `.invoke(query)` - `.get_relevant_documents(query, callbacks=callbacks)` -> `.invoke(query, config={"callbacks": callbacks})` - `.get_relevant_documents(query, kwargs)` -> `.invoke(query, kwargs)` --------- Co-authored-by: Erick Friis <erick@langchain.dev>	5 months ago
Bagatur	1c7b3c75a7	community[patch], experimental[patch]: support tool-calling sql and p… (#20639 ) d agents	5 months ago
Leonid Ganeline	95dc90609e	experimental[patch]: `prompts` import fix (#20534 ) Replaced `from langchain.prompts` with `from langchain_core.prompts` where it is appropriate. Most of the changes go to `langchain_experimental` Similar to #20348	5 months ago
ccurme	38faa74c23	community[patch]: update use of deprecated llm methods (#20393 ) .predict and .predict_messages for BaseLanguageModel and BaseChatModel	5 months ago
Leonid Ganeline	e512d3c6a6	langchain: `callbacks` imports fix (#20348 ) Replaced all `from langchain.callbacks` into `from langchain_core.callbacks` . Changes in the `langchain` and `langchain_experimental` --------- Co-authored-by: Erick Friis <erick@langchain.dev>	5 months ago
Tomaz Bratanic	a1b105ac00	experimental[patch]: Skip pydantic validation for llm graph transformer and fix JSON response where possible (#19915 ) LLMs might sometimes return invalid response for LLM graph transformer. Instead of failing due to pydantic validation, we skip it and manually check and optionally fix error where we can, so that more information gets extracted	5 months ago
Bagatur	2d83505be9	experimental[patch]: Release 0.0.57 (#20243 )	5 months ago
Erick Friis	f0d5b59962	core[patch]: remove requests (#19891 ) Removes required usage of `requests` from `langchain-core`, all of which has been deprecated. - removes Tracer V1 implementations - removes old `try_load_from_hub` github-based hub implementations Removal done in a way where imports will still succeed, and usage will fail with a `RuntimeError`.	5 months ago
Bagatur	003c98e5b4	experimental[patch]: Release 0.0.56 (#19840 )	6 months ago
LunarECL	b7d180a70d	experimental[minor]: Create Closed Captioning Chain for .mp4 videos (#14059 ) Description: Video imagery to text (Closed Captioning) This pull request introduces the VideoCaptioningChain, a tool for automated video captioning. It processes audio and video to generate subtitles and closed captions, merging them into a single SRT output. Issue: https://github.com/langchain-ai/langchain/issues/11770 Dependencies: opencv-python, ffmpeg-python, assemblyai, transformers, pillow, torch, openai Tag maintainer: @baskaryan @hwchase17 Hello!  We are a group of students from the University of Toronto (@LunarECL, @TomSadan, @nicoledroi1, @A2113S) that want to make a contribution to the LangChain community! We have ran make format, make lint and make test locally before submitting the PR. To our knowledge, our changes do not introduce any new errors. Thank you for taking the time to review our PR! --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
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
T Cramer	540ebf35a9	community[patch]: Add explicit error message to Bedrock error output. (#17328 ) - Description: Propagate Bedrock errors into Langchain explicitly. Use-case: unset region error is hidden behind 'Could not load credentials...' message - Issue: [17654](https://github.com/langchain-ai/langchain/issues/17654) - Dependencies: None --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	6 months ago
Luca Dorigo	f19229c564	core[patch]: fix beta, deprecated typing (#18877 ) Description: While not technically incorrect, the TypeVar used for the `@beta` decorator prevented pyright (and thus most vscode users) from correctly seeing the types of functions/classes decorated with `@beta`. This is in part due to a small bug in pyright (https://github.com/microsoft/pyright/issues/7448 ) - however, the `Type` bound in the typevar `C = TypeVar("C", Type, Callable)` is not doing anything - classes are `Callables` by default, so by my understanding binding to `Type` does not actually provide any more safety - the modified annotation still works correctly for both functions, properties, and classes. --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago

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286 Commits (9ac302cb97cbf9392ab8c37309873b069e277176)