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Author	SHA1	Message	Date
Mateusz Szewczyk	9298a0b941	langchain_ibm[patch] update docstring, dependencies, tests (#18386) ... - **Description:** Update docstring, dependencies, tests, README - **Dependencies:** [ibm-watsonx-ai](https://pypi.org/project/ibm-watsonx-ai/), - **Tag maintainer:** : Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally -> ✅ Please make sure integration_tests passing locally -> ✅ --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Jib	c2b1abe91b	mongodb[patch]: Set delete_many only if count_documents is not 0 (#18402) ... - [x] **PR message**: ***Delete this entire checklist*** and replace with - **Description:** Remove the assert statement on the `count_documents` in setup_class. It should just delete if there are documents present - **Issue:** the issue # Crashes on class setup - **Dependencies:** None - **Twitter handle:** @mongodb - [x] **Add tests and docs**: If you're adding a new integration, please include 1. N/A - [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17. Co-authored-by: Jib <jib@byblack.us>	6 months ago
Kate Silverstein	c9153a3fd4	docs: add llamafile info to 'Local LLMs' guides (#18049) ... - **Description:** add information about [llamafile](https://github.com/Mozilla-Ocho/llamafile) (setup, example usage) to ['Run LLMs locally'](https://python.langchain.com/docs/guides/local_llms) and ['Using local models for Q&A with RAG'](https://python.langchain.com/docs/use_cases/question_answering/local_retrieval_qa) guides. - **Issue:** N/A - **Dependencies:** N/A	6 months ago
Tomaz Bratanic	f6bfb969ba	community[patch]: Add an option for indexed generic label when import neo4j graph documents (#18122) ... Current implementation doesn't have an indexed property that would optimize the import. I have added a `baseEntityLabel` parameter that allows you to add a secondary node label, which has an indexed id `property`. By default, the behaviour is identical to previous version. Since multi-labeled nodes are terrible for text2cypher, I removed the secondary label from schema representation object and string, which is used in text2cypher.	6 months ago
aditya thomas	e6e60e2492	docs: ChatOpenAI update module import path and calling method (#18169) ... **Description:** (a) Update to the module import path to reflect the splitting up of langchain into separate packages (b) Update to the documentation to include the new calling method (invoke)	6 months ago
Arun Sathiya	4adac20d7b	community[patch]: Make cohere_api_key a SecretStr (#12188) ... This PR makes `cohere_api_key` in `llms/cohere` a SecretStr, so that the API Key is not leaked when `Cohere.cohere_api_key` is represented as a string. --------- Signed-off-by: Arun <arun@arun.blog> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	6 months ago
Ryan Meinzer	d883fd4a37	docs: Correct WebBaseLoader URL: docs: python.langchain.com/docs/get_started/quickstartQuickstart (#17981) ... **Description:** The URL of the data to index, specified to `WebBaseLoader` to import is incorrect, causing the `langsmith_search` retriever to return a `404: NOT_FOUND`. Incorrect URL: https://docs.smith.langchain.com/overview Correct URL: https://docs.smith.langchain.com **Issue:** This commit corrects the URL and prevents the LangServe Playground from returning an error from its inability to use the retriever when inquiring, "how can langsmith help with testing?". **Dependencies:** None. **Twitter Handle:** @ryanmeinzer	6 months ago
Petteri Johansson	6c1989d292	community[minor], langchain[minor], docs: Gremlin Graph Store and QA Chain (#17683) ... - **Description:** New feature: Gremlin graph-store and QA chain (including docs). Compatible with Azure CosmosDB. - **Dependencies:** no changes	6 months ago
Ather Fawaz	a5ccf5d33c	community[minor]: Add support for Perplexity chat model(#17024) ... - **Description:** This PR adds support for [Perplexity AI APIs](https://blog.perplexity.ai/blog/introducing-pplx-api). - **Issues:** None - **Dependencies:** None - **Twitter handle:** [@atherfawaz](https://twitter.com/AtherFawaz) --------- Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Rodrigo Nogueira	3438d2cbcc	community[minor]: add maritalk chat (#17675) ... **Description:** Adds the MariTalk chat that is based on a LLM specially trained for Portuguese. **Twitter handle:** @MaritacaAI	6 months ago
sarahberenji	08fa38d56d	community[patch]: the syntax error for Redis generated query (#17717) ... To fix the reported error: https://github.com/langchain-ai/langchain/discussions/17397	6 months ago
certified-dodo	43e3244573	community[patch]: Fix MongoDBAtlasVectorSearch max_marginal_relevance_search (#17971) ... Description: * `self._embedding_key` is accessed after deletion, breaking `max_marginal_relevance_search` search * Introduced in: e135e5257c * Updated but still persists in: ce22e10c4b Issue: https://github.com/langchain-ai/langchain/issues/17963 Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Nikita Titov	9f2ab37162	community[patch]: don't try to parse json in case of errored response (#18317) ... Related issue: #13896. In case Ollama is behind a proxy, proxy error responses cannot be viewed. You aren't even able to check response code. For example, if your Ollama has basic access authentication and it's not passed, `JSONDecodeError` will overwrite the truth response error. <details> <summary><b>Log now:</b></summary> ``` { "name": "JSONDecodeError", "message": "Expecting value: line 1 column 1 (char 0)", "stack": "--------------------------------------------------------------------------- JSONDecodeError Traceback (most recent call last) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/requests/models.py:971, in Response.json(self, **kwargs) 970 try: --> 971 return complexjson.loads(self.text, **kwargs) 972 except JSONDecodeError as e: 973 # Catch JSON-related errors and raise as requests.JSONDecodeError 974 # This aliases json.JSONDecodeError and simplejson.JSONDecodeError File /opt/miniforge3/envs/.gpt/lib/python3.10/json/__init__.py:346, in loads(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw) 343 if (cls is None and object_hook is None and 344 parse_int is None and parse_float is None and 345 parse_constant is None and object_pairs_hook is None and not kw): --> 346 return _default_decoder.decode(s) 347 if cls is None: File /opt/miniforge3/envs/.gpt/lib/python3.10/json/decoder.py:337, in JSONDecoder.decode(self, s, _w) 333 \"\"\"Return the Python representation of ``s`` (a ``str`` instance 334 containing a JSON document). 335 336 \"\"\" --> 337 obj, end = self.raw_decode(s, idx=_w(s, 0).end()) 338 end = _w(s, end).end() File /opt/miniforge3/envs/.gpt/lib/python3.10/json/decoder.py:355, in JSONDecoder.raw_decode(self, s, idx) 354 except StopIteration as err: --> 355 raise JSONDecodeError(\"Expecting value\", s, err.value) from None 356 return obj, end JSONDecodeError: Expecting value: line 1 column 1 (char 0) During handling of the above exception, another exception occurred: JSONDecodeError Traceback (most recent call last) Cell In[3], line 1 ----> 1 print(translate_func().invoke('text')) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/runnables/base.py:2053, in RunnableSequence.invoke(self, input, config) 2051 try: 2052 for i, step in enumerate(self.steps): -> 2053 input = step.invoke( 2054 input, 2055 # mark each step as a child run 2056 patch_config( 2057 config, callbacks=run_manager.get_child(f\"seq:step:{i+1}\") 2058 ), 2059 ) 2060 # finish the root run 2061 except BaseException as e: File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:165, in BaseChatModel.invoke(self, input, config, stop, **kwargs) 154 def invoke( 155 self, 156 input: LanguageModelInput, (...) 160 **kwargs: Any, 161 ) -> BaseMessage: 162 config = ensure_config(config) 163 return cast( 164 ChatGeneration, --> 165 self.generate_prompt( 166 [self._convert_input(input)], 167 stop=stop, 168 callbacks=config.get(\"callbacks\"), 169 tags=config.get(\"tags\"), 170 metadata=config.get(\"metadata\"), 171 run_name=config.get(\"run_name\"), 172 **kwargs, 173 ).generations[0][0], 174 ).message File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:543, in BaseChatModel.generate_prompt(self, prompts, stop, callbacks, **kwargs) 535 def generate_prompt( 536 self, 537 prompts: List[PromptValue], (...) 540 **kwargs: Any, 541 ) -> LLMResult: 542 prompt_messages = [p.to_messages() for p in prompts] --> 543 return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:407, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs) 405 if run_managers: 406 run_managers[i].on_llm_error(e, response=LLMResult(generations=[])) --> 407 raise e 408 flattened_outputs = [ 409 LLMResult(generations=[res.generations], llm_output=res.llm_output) 410 for res in results 411 ] 412 llm_output = self._combine_llm_outputs([res.llm_output for res in results]) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:397, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs) 394 for i, m in enumerate(messages): 395 try: 396 results.append( --> 397 self._generate_with_cache( 398 m, 399 stop=stop, 400 run_manager=run_managers[i] if run_managers else None, 401 **kwargs, 402 ) 403 ) 404 except BaseException as e: 405 if run_managers: File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:576, in BaseChatModel._generate_with_cache(self, messages, stop, run_manager, **kwargs) 572 raise ValueError( 573 \"Asked to cache, but no cache found at `langchain.cache`.\" 574 ) 575 if new_arg_supported: --> 576 return self._generate( 577 messages, stop=stop, run_manager=run_manager, **kwargs 578 ) 579 else: 580 return self._generate(messages, stop=stop, **kwargs) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/chat_models/ollama.py:250, in ChatOllama._generate(self, messages, stop, run_manager, **kwargs) 226 def _generate( 227 self, 228 messages: List[BaseMessage], (...) 231 **kwargs: Any, 232 ) -> ChatResult: 233 \"\"\"Call out to Ollama's generate endpoint. 234 235 Args: (...) 247 ]) 248 \"\"\" --> 250 final_chunk = self._chat_stream_with_aggregation( 251 messages, 252 stop=stop, 253 run_manager=run_manager, 254 verbose=self.verbose, 255 **kwargs, 256 ) 257 chat_generation = ChatGeneration( 258 message=AIMessage(content=final_chunk.text), 259 generation_info=final_chunk.generation_info, 260 ) 261 return ChatResult(generations=[chat_generation]) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/chat_models/ollama.py:183, in ChatOllama._chat_stream_with_aggregation(self, messages, stop, run_manager, verbose, **kwargs) 174 def _chat_stream_with_aggregation( 175 self, 176 messages: List[BaseMessage], (...) 180 **kwargs: Any, 181 ) -> ChatGenerationChunk: 182 final_chunk: Optional[ChatGenerationChunk] = None --> 183 for stream_resp in self._create_chat_stream(messages, stop, **kwargs): 184 if stream_resp: 185 chunk = _chat_stream_response_to_chat_generation_chunk(stream_resp) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/chat_models/ollama.py:156, in ChatOllama._create_chat_stream(self, messages, stop, **kwargs) 147 def _create_chat_stream( 148 self, 149 messages: List[BaseMessage], 150 stop: Optional[List[str]] = None, 151 **kwargs: Any, 152 ) -> Iterator[str]: 153 payload = { 154 \"messages\": self._convert_messages_to_ollama_messages(messages), 155 } --> 156 yield from self._create_stream( 157 payload=payload, stop=stop, api_url=f\"{self.base_url}/api/chat/\", **kwargs 158 ) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/llms/ollama.py:234, in _OllamaCommon._create_stream(self, api_url, payload, stop, **kwargs) 228 raise OllamaEndpointNotFoundError( 229 \"Ollama call failed with status code 404. \" 230 \"Maybe your model is not found \" 231 f\"and you should pull the model with `ollama pull {self.model}`.\" 232 ) 233 else: --> 234 optional_detail = response.json().get(\"error\") 235 raise ValueError( 236 f\"Ollama call failed with status code {response.status_code}.\" 237 f\" Details: {optional_detail}\" 238 ) 239 return response.iter_lines(decode_unicode=True) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/requests/models.py:975, in Response.json(self, **kwargs) 971 return complexjson.loads(self.text, **kwargs) 972 except JSONDecodeError as e: 973 # Catch JSON-related errors and raise as requests.JSONDecodeError 974 # This aliases json.JSONDecodeError and simplejson.JSONDecodeError --> 975 raise RequestsJSONDecodeError(e.msg, e.doc, e.pos) JSONDecodeError: Expecting value: line 1 column 1 (char 0)" } ``` </details> <details> <summary><b>Log after a fix:</b></summary> ``` { "name": "ValueError", "message": "Ollama call failed with status code 401. Details: <html>\r <head><title>401 Authorization Required</title></head>\r <body>\r <center><h1>401 Authorization Required</h1></center>\r <hr><center>nginx/1.18.0 (Ubuntu)</center>\r </body>\r </html>\r ", "stack": "--------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[2], line 1 ----> 1 print(translate_func().invoke('text')) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/runnables/base.py:2053, in RunnableSequence.invoke(self, input, config) 2051 try: 2052 for i, step in enumerate(self.steps): -> 2053 input = step.invoke( 2054 input, 2055 # mark each step as a child run 2056 patch_config( 2057 config, callbacks=run_manager.get_child(f\"seq:step:{i+1}\") 2058 ), 2059 ) 2060 # finish the root run 2061 except BaseException as e: File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:165, in BaseChatModel.invoke(self, input, config, stop, **kwargs) 154 def invoke( 155 self, 156 input: LanguageModelInput, (...) 160 **kwargs: Any, 161 ) -> BaseMessage: 162 config = ensure_config(config) 163 return cast( 164 ChatGeneration, --> 165 self.generate_prompt( 166 [self._convert_input(input)], 167 stop=stop, 168 callbacks=config.get(\"callbacks\"), 169 tags=config.get(\"tags\"), 170 metadata=config.get(\"metadata\"), 171 run_name=config.get(\"run_name\"), 172 **kwargs, 173 ).generations[0][0], 174 ).message File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:543, in BaseChatModel.generate_prompt(self, prompts, stop, callbacks, **kwargs) 535 def generate_prompt( 536 self, 537 prompts: List[PromptValue], (...) 540 **kwargs: Any, 541 ) -> LLMResult: 542 prompt_messages = [p.to_messages() for p in prompts] --> 543 return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:407, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs) 405 if run_managers: 406 run_managers[i].on_llm_error(e, response=LLMResult(generations=[])) --> 407 raise e 408 flattened_outputs = [ 409 LLMResult(generations=[res.generations], llm_output=res.llm_output) 410 for res in results 411 ] 412 llm_output = self._combine_llm_outputs([res.llm_output for res in results]) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:397, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs) 394 for i, m in enumerate(messages): 395 try: 396 results.append( --> 397 self._generate_with_cache( 398 m, 399 stop=stop, 400 run_manager=run_managers[i] if run_managers else None, 401 **kwargs, 402 ) 403 ) 404 except BaseException as e: 405 if run_managers: File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:576, in BaseChatModel._generate_with_cache(self, messages, stop, run_manager, **kwargs) 572 raise ValueError( 573 \"Asked to cache, but no cache found at `langchain.cache`.\" 574 ) 575 if new_arg_supported: --> 576 return self._generate( 577 messages, stop=stop, run_manager=run_manager, **kwargs 578 ) 579 else: 580 return self._generate(messages, stop=stop, **kwargs) File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/chat_models/ollama.py:250, in ChatOllama._generate(self, messages, stop, run_manager, **kwargs) 226 def _generate( 227 self, 228 messages: List[BaseMessage], (...) 231 **kwargs: Any, 232 ) -> ChatResult: 233 \"\"\"Call out to Ollama's generate endpoint. 234 235 Args: (...) 247 ]) 248 \"\"\" --> 250 final_chunk = self._chat_stream_with_aggregation( 251 messages, 252 stop=stop, 253 run_manager=run_manager, 254 verbose=self.verbose, 255 **kwargs, 256 ) 257 chat_generation = ChatGeneration( 258 message=AIMessage(content=final_chunk.text), 259 generation_info=final_chunk.generation_info, 260 ) 261 return ChatResult(generations=[chat_generation]) File /storage/gpt-project/Repos/repo_nikita/gpt_lib/langchain/ollama.py:328, in ChatOllamaCustom._chat_stream_with_aggregation(self, messages, stop, run_manager, verbose, **kwargs) 319 def _chat_stream_with_aggregation( 320 self, 321 messages: List[BaseMessage], (...) 325 **kwargs: Any, 326 ) -> ChatGenerationChunk: 327 final_chunk: Optional[ChatGenerationChunk] = None --> 328 for stream_resp in self._create_chat_stream(messages, stop, **kwargs): 329 if stream_resp: 330 chunk = _chat_stream_response_to_chat_generation_chunk(stream_resp) File /storage/gpt-project/Repos/repo_nikita/gpt_lib/langchain/ollama.py:301, in ChatOllamaCustom._create_chat_stream(self, messages, stop, **kwargs) 292 def _create_chat_stream( 293 self, 294 messages: List[BaseMessage], 295 stop: Optional[List[str]] = None, 296 **kwargs: Any, 297 ) -> Iterator[str]: 298 payload = { 299 \"messages\": self._convert_messages_to_ollama_messages(messages), 300 } --> 301 yield from self._create_stream( 302 payload=payload, stop=stop, api_url=f\"{self.base_url}/api/chat\", **kwargs 303 ) File /storage/gpt-project/Repos/repo_nikita/gpt_lib/langchain/ollama.py:134, in _OllamaCommonCustom._create_stream(self, api_url, payload, stop, **kwargs) 132 else: 133 optional_detail = response.text --> 134 raise ValueError( 135 f\"Ollama call failed with status code {response.status_code}.\" 136 f\" Details: {optional_detail}\" 137 ) 138 return response.iter_lines(decode_unicode=True) ValueError: Ollama call failed with status code 401. Details: <html>\r <head><title>401 Authorization Required</title></head>\r <body>\r <center><h1>401 Authorization Required</h1></center>\r <hr><center>nginx/1.18.0 (Ubuntu)</center>\r </body>\r </html>\r " } ``` </details> The same is true for timeout errors or when you simply mistyped in `base_url` arg and get response from some other service, for instance. Real Ollama errors are still clearly readable: ``` ValueError: Ollama call failed with status code 400. Details: {"error":"invalid options: unknown_option"} ``` --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Yudhajit Sinha	e2b901c35b	community[patch]: chat message histrory mypy fix (#18250) ... Description: Fixed type: ignore's for mypy for chat_message_histories(streamlit) Adresses #17048 Planning to add more based on reviews	6 months ago
Gabriel Altay	b9416dc96a	docs: update pinecone README to use PineconeVectorStore (#18170)	6 months ago
老阿張	1701f7b8e9	docs: Fix typo in baidu_qianfan_endpoint.ipynb & baidu_qianfan_endpoint.ipynb (#18176) ... Description: "sucessfully should be successfully "? 🤔 Issue: Typo Dependencies: Nope Twitter handle: laoazhang	6 months ago
Hemslo Wang	58a2abf089	community[patch]: fix RecursiveUrlLoader metadata_extractor return type (#18193) ... **Description:** Fix `metadata_extractor` type for `RecursiveUrlLoader`, the default `_metadata_extractor` returns `dict` instead of `str`. **Issue:** N/A **Dependencies:** N/A **Twitter handle:** N/A Signed-off-by: Hemslo Wang <hemslo.wang@gmail.com>	6 months ago
Maxime Perrin	98380cff9b	community[patch]: removing "response_mode" parameter in llama_index retriever (#18180) ... - **Description:** Removing this line ```python response = index.query(query, response_mode="no_text", **self.query_kwargs) ``` to ```python response = index.query(query, **self.query_kwargs) ``` Since llama index query does not support response_mode anymore : ``` | TypeError: BaseQueryEngine.query() got an unexpected keyword argument 'response_mode'```` - **Twitter handle:** @maximeperrin_ --------- Co-authored-by: Maxime Perrin <mperrin@doing.fr>	6 months ago
Leonid Kuligin	e080281623	docs: cookbook on gemma integrations (#18213) ... - [ ] **PR title**: "cookbook: using Gemma on LangChain" - [ ] **PR message**: - **Description:** added a tutorial how to use Gemma with LangChain (from VertexAI or locally from Kaggle or HF) - **Dependencies:** langchain-google-vertexai==0.0.7 - **Twitter handle:** lkuligin	6 months ago
Christophe Bornet	177f51c7bd	community: Use default load() implementation in doc loaders (#18385) ... Following https://github.com/langchain-ai/langchain/pull/18289	6 months ago
William De Vena	42341bc787	infra: fake model invoke callback prior to yielding token (#18286) ... ## PR title core[patch]: Invoke callback prior to yielding ## PR message Description: Invoke on_llm_new_token callback prior to yielding token in _stream and _astream methods. Issue: https://github.com/langchain-ai/langchain/issues/16913 Dependencies: None Twitter handle: None	6 months ago
Ikko Eltociear Ashimine	31b4e78174	docs: fix typo in milvus.ipynb (#18373) ... retreival -> retrieval	6 months ago
Tabby	dd6f85caf1	docs: Update Google El Carro for Oracle Workload Documentation. (#18394) ... In this commit we update the documentation for Google El Carro for Oracle Workloads. We amend the documentation in the Google Providers page to use the correct name which is El Carro for Oracle Workloads. We also add changes to the document_loaders and memory pages to reflect changes we made in our repo.	6 months ago
mwmajewsk	e192f6b6eb	community[patch]: fix, better error message in deeplake vectoriser (#18397) ... If the document loader recieves Pathlib path instead of str, it reads the file correctly, but the problem begins when the document is added to Deeplake. This problem arises from casting the path to str in the metadata. ```python deeplake = True fname = Path('./lorem_ipsum.txt') loader = TextLoader(fname, encoding="utf-8") docs = loader.load_and_split() text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=100) chunks= text_splitter.split_documents(docs) if deeplake: db = DeepLake(dataset_path=ds_path, embedding=embeddings, token=activeloop_token) db.add_documents(chunks) else: db = Chroma.from_documents(docs, embeddings) ``` So using this snippet of code the error message for deeplake looks like this: ``` [part of error message omitted] Traceback (most recent call last): File "/home/mwm/repositories/sources/fixing_langchain/main.py", line 53, in <module> db.add_documents(chunks) File "/home/mwm/repositories/sources/langchain/libs/core/langchain_core/vectorstores.py", line 139, in add_documents return self.add_texts(texts, metadatas, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/mwm/repositories/sources/langchain/libs/community/langchain_community/vectorstores/deeplake.py", line 258, in add_texts return self.vectorstore.add( ^^^^^^^^^^^^^^^^^^^^^ File "/home/mwm/anaconda3/envs/langchain/lib/python3.11/site-packages/deeplake/core/vectorstore/deeplake_vectorstore.py", line 226, in add return self.dataset_handler.add( ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/mwm/anaconda3/envs/langchain/lib/python3.11/site-packages/deeplake/core/vectorstore/dataset_handlers/client_side_dataset_handler.py", line 139, in add dataset_utils.extend_or_ingest_dataset( File "/home/mwm/anaconda3/envs/langchain/lib/python3.11/site-packages/deeplake/core/vectorstore/vector_search/dataset/dataset.py", line 544, in extend_or_ingest_dataset extend( File "/home/mwm/anaconda3/envs/langchain/lib/python3.11/site-packages/deeplake/core/vectorstore/vector_search/dataset/dataset.py", line 505, in extend dataset.extend(batched_processed_tensors, progressbar=False) File "/home/mwm/anaconda3/envs/langchain/lib/python3.11/site-packages/deeplake/core/dataset/dataset.py", line 3247, in extend raise SampleExtendError(str(e)) from e.__cause__ deeplake.util.exceptions.SampleExtendError: Failed to append a sample to the tensor 'metadata'. See more details in the traceback. If you wish to skip the samples that cause errors, please specify `ignore_errors=True`. ``` Which is does not explain the error well enough. The same error for chroma looks like this ``` During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/mwm/repositories/sources/fixing_langchain/main.py", line 56, in <module> db = Chroma.from_documents(docs, embeddings) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/mwm/repositories/sources/langchain/libs/community/langchain_community/vectorstores/chroma.py", line 778, in from_documents return cls.from_texts( ^^^^^^^^^^^^^^^ File "/home/mwm/repositories/sources/langchain/libs/community/langchain_community/vectorstores/chroma.py", line 736, in from_texts chroma_collection.add_texts( File "/home/mwm/repositories/sources/langchain/libs/community/langchain_community/vectorstores/chroma.py", line 309, in add_texts raise ValueError(e.args[0] + "\n\n" + msg) ValueError: Expected metadata value to be a str, int, float or bool, got lorem_ipsum.txt which is a <class 'pathlib.PosixPath'> Try filtering complex metadata from the document using langchain_community.vectorstores.utils.filter_complex_metadata. ``` Which is way more user friendly, so I just added information about possible mismatch of the type in the error message, the same way it is covered in chroma https://github.com/langchain-ai/langchain/blob/master/libs/community/langchain_community/vectorstores/chroma.py#L224	6 months ago
Daniel Chico	7d962278f6	community[patch]: type ignore fixes (#18395) ... Related to #17048	6 months ago
Christophe Bornet	69be82c86d	community[patch]: Implement lazy_load() for CSVLoader (#18391) ... Covered by `test_csv_loader.py`	6 months ago
Bagatur	c54d6eb5da	fireworks[patch]: support "any" tool_choice (#18343) ... per https://readme.fireworks.ai/docs/function-calling	6 months ago
Leonid Ganeline	d937fa4f9c	docs: `Tutorials` update (#18230) ... A big update of the `Tutorials` page. Cleaned it up. Added several new resources.	6 months ago
Erick Friis	6afb135baa	astradb: move to langchain-datastax repo (#18354)	6 months ago
Akash A Desai	b641be2edf	templates: Lanceb RAG template (#17809) ... Thank you for contributing to LangChain! - [x] **PR title**: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [x] **PR message**: ***Delete this entire checklist*** and replace with - **Description:** a description of the change - **Issue:** the issue # it fixes, if applicable - **Dependencies:** any dependencies required for this change - **Twitter handle:** if your PR gets announced, and you'd like a mention, we'll gladly shout you out! - [x] **Add tests and docs**: 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. - [x] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Guangdong Liu	760a16ff32	community[patch]: Fix ChatModel for sparkllm Bug. (#18375) ... **PR message**: ***Delete this entire checklist*** and replace with - **Description:** fix sparkllm paramer error - **Issue:** close #18370 - **Dependencies:** change `IFLYTEK_SPARK_APP_URL` to `IFLYTEK_SPARK_API_URL` - **Twitter handle:** No	6 months ago
Yujie Qian	cbb65741a7	community[patch]: Voyage AI updates default model and batch size (#17655) ... - **Description:** update the default model and batch size in VoyageEmbeddings - **Issue:** N/A - **Dependencies:** N/A - **Twitter handle:** N/A --------- Co-authored-by: fodizoltan <zoltan@conway.expert>	6 months ago
Shengsheng Huang	ae471a7dcb	community[minor]: add BigDL-LLM integrations (#17953) ... - **Description**: [`bigdl-llm`](https://github.com/intel-analytics/BigDL) is a library for running LLM on Intel XPU (from Laptop to GPU to Cloud) using INT4/FP4/INT8/FP8 with very low latency (for any PyTorch model). This PR adds bigdl-llm integrations to langchain. - **Issue**: NA - **Dependencies**: `bigdl-llm` library - **Contribution maintainer**: @shane-huang Examples added: - docs/docs/integrations/llms/bigdl.ipynb	6 months ago
Ethan Yang	f61cb8d407	community[minor]: Add openvino backend support (#11591) ... - **Description:** add openvino backend support by HuggingFace Optimum Intel, - **Dependencies:** “optimum[openvino]”, --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Leonid Ganeline	a89f007947	docs: `runnable` module description (#17966) ... Added a module description. Added `batch` description.	6 months ago
Leonid Ganeline	6d0af4e805	docs: nvidia: provider page update (#18054) ... Nvidia provider page is missing a Triton Inference Server package reference. Changes: - added the Triton Inference Server reference - copied the example notebook from the package into the doc files. - added the Triton Inference Server description and links, the link to the above example notebook - formatted page to the consistent format NOTE: It seems that the [example notebook](https://github.com/langchain-ai/langchain/blob/master/libs/partners/nvidia-trt/docs/llms.ipynb) was originally created in wrong place. It should be in the LangChain docs [here](https://github.com/langchain-ai/langchain/tree/master/docs/docs/integrations/llms). So, I've created a copy of this example. The original example is still in the nvidia-trt package.	6 months ago
RadhikaBansal97	8bafd2df5e	community[patch]: Change github endpoint in GithubLoader (#17622) ... Description- - Changed the GitHub endpoint as existing was not working and giving 404 not found error - Also the existing function was failing if file_filter is not passed as the tree api return all paths including directory as well, and when get_file_content was iterating over these path, the function was failing for directory as the api was returning list of files inside the directory, so added a condition to ignore the paths if it a directory - Fixes this issue - https://github.com/langchain-ai/langchain/issues/17453 Co-authored-by: Radhika Bansal <Radhika.Bansal@veritas.com>	6 months ago
Yufei (Benny) Chen	2b93206f02	fireworks[patch]: Fix fireworks async stream (#18372) ... - **Description:** Fix the async stream issue with Fireworks - **Dependencies:** fireworks >= 0.13.0 ``` tests/integration_tests/test_chat_models.py .......... [ 45%] tests/integration_tests/test_compile.py . [ 50%] tests/integration_tests/test_embeddings.py .. [ 59%] tests/integration_tests/test_llms.py ......... [100%] ``` ``` tests/unit_tests/test_embeddings.py . [ 16%] tests/unit_tests/test_imports.py . [ 33%] tests/unit_tests/test_llms.py .... [100%] ``` --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
William FH	1deb8cadd5	Add dataset version info (#18299)	6 months ago
Anush	9d663f31fa	community[patch]: FastEmbed to latest (#18040) ... ## Description Updates the `langchain_community.embeddings.fastembed` provider as per the recent updates to [`FastEmbed`](https://github.com/qdrant/fastembed) library.	6 months ago
Jacob Lee	590d47bff4	docs[patch]: Add Neo4j GraphAcademy to tutorials section (#18353)	6 months ago
Erick Friis	3c8a115e21	fireworks[patch]: remove custom async and stream implementations (#18363)	6 months ago
Bagatur	4730ee2766	docs: update api ref nav (#18362)	6 months ago
Bagatur	12f19b8a6a	infra: update create_api_rst (#18361)	6 months ago
Erick Friis	1317578ad1	templates: use langchain-text-splitters (#18360) ... - deps - import - import	6 months ago
Bagatur	f220af3dce	docs: text splitters readme (#18359)	6 months ago
Bagatur	0d7fb5f60a	langchain[patch]: langchain-text-splitters dep (#18357)	6 months ago
Eugene Yurtsev	51b661cfe8	community[patch]: BaseLoader load method should just delegate to lazy_load (#18289) ... load() should just reference lazy_load()	6 months ago
Bagatur	5efb5c099f	text-splitters[minor], langchain[minor], community[patch], templates, docs: langchain-text-splitters 0.0.1 (#18346)	6 months ago
Nuno Campos	7891934173	Fix missing labels (#18356) ... Thank you for contributing to LangChain! - [ ] **PR title**: "package: description" - Where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes. - Example: "community: add foobar LLM" - [ ] **PR message**: ***Delete this entire checklist*** and replace with - **Description:** a description of the change - **Issue:** the issue # it fixes, if applicable - **Dependencies:** any dependencies required for this change - **Twitter handle:** if your PR gets announced, and you'd like a mention, we'll gladly shout you out! - [ ] **Add tests and docs**: 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. - [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/ Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17.	6 months ago