485 Commits (c8a171a154ed8c953ea26dc161efbc788942bff9)

Author	SHA1	Message	Date
Christophe Bornet	c8a171a154	community: Implement lazy_load() for GithubFileLoader (#18584)	6 months ago
Leonid Kuligin	04d134df17	marked MatchingEngine as deprecated (#18585) ... Thank you for contributing to LangChain! - [ ] **PR title**: "community: deprecate vectorstores.MatchingEngine" - [ ] **PR message**: - **Description:** announced a deprecation since this integration has been moved to langchain_google_vertexai	6 months ago
Erick Friis	343438e872	community[patch]: deprecate community fireworks (#18544)	6 months ago
Scott Nath	b051bba1a9	community: Add you.com tool, add async to retriever, add async testing, add You tool doc (#18032) ... - **Description:** finishes adding the you.com functionality including: - add async functions to utility and retriever - add the You.com Tool - add async testing for utility, retriever, and tool - add a tool integration notebook page - **Dependencies:** any dependencies required for this change - **Twitter handle:** @scottnath	6 months ago
William De Vena	275877980e	community[patch]: Invoke callback prior to yielding token (#18447) ... ## PR title community[patch]: Invoke callback prior to yielding token ## PR message Description: Invoke callback prior to yielding token in _stream method in llms/vertexai. Issue: https://github.com/langchain-ai/langchain/issues/16913 Dependencies: None	6 months ago
William De Vena	67375e96e0	community[patch]: Invoke callback prior to yielding token (#18448) ... ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream method in llms/tongyi. - Issue: https://github.com/langchain-ai/langchain/issues/16913 - Dependencies: None	6 months ago
William De Vena	2087cbae64	community[patch]: Invoke callback prior to yielding token (#18449) ... ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream method in chat_models/perplexity. - Issue: https://github.com/langchain-ai/langchain/issues/16913 - Dependencies: None	6 months ago
William De Vena	eb04d0d3e2	community[patch]: Invoke callback prior to yielding token (#18452) ... ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream and _astream methods in llms/anthropic. - Issue: https://github.com/langchain-ai/langchain/issues/16913 - Dependencies: None	6 months ago
William De Vena	371bec79bc	community[patch]: Invoke callback prior to yielding token (#18454) ... ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream and _astream methods in llms/baidu_qianfan_endpoint. - Issue: https://github.com/langchain-ai/langchain/issues/16913 - Dependencies: None	6 months ago
Aayush Kataria	7c2f3f6f95	community[minor]: Adding Azure Cosmos Mongo vCore Vector DB Cache (#16856) ... Description: This pull request introduces several enhancements for Azure Cosmos Vector DB, primarily focused on improving caching and search capabilities using Azure Cosmos MongoDB vCore Vector DB. Here's a summary of the changes: - **AzureCosmosDBSemanticCache**: Added a new cache implementation called AzureCosmosDBSemanticCache, which utilizes Azure Cosmos MongoDB vCore Vector DB for efficient caching of semantic data. Added comprehensive test cases for AzureCosmosDBSemanticCache to ensure its correctness and robustness. These tests cover various scenarios and edge cases to validate the cache's behavior. - **HNSW Vector Search**: Added HNSW vector search functionality in the CosmosDB Vector Search module. This enhancement enables more efficient and accurate vector searches by utilizing the HNSW (Hierarchical Navigable Small World) algorithm. Added corresponding test cases to validate the HNSW vector search functionality in both AzureCosmosDBSemanticCache and AzureCosmosDBVectorSearch. These tests ensure the correctness and performance of the HNSW search algorithm. - **LLM Caching Notebook** - The notebook now includes a comprehensive example showcasing the usage of the AzureCosmosDBSemanticCache. This example highlights how the cache can be employed to efficiently store and retrieve semantic data. Additionally, the example provides default values for all parameters used within the AzureCosmosDBSemanticCache, ensuring clarity and ease of understanding for users who are new to the cache implementation. @hwchase17,@baskaryan, @eyurtsev,	6 months ago
Sourav Pradhan	50abeb7ed9	community[patch]: fix Chroma add_images (#17964) ... ### Description Fixed a small bug in chroma.py add_images(), previously whenever we are not passing metadata the documents is containing the base64 of the uris passed, but when we are passing the metadata the documents is containing normal string uris which should not be the case. ### Issue In add_images() method when we are calling upsert() we have to use "b64_texts" instead of normal string "uris". ### Twitter handle https://twitter.com/whitepegasus01	6 months ago
Kate Silverstein	b7c71e2e07	community[minor]: llamafile embeddings support (#17976) ... * **Description:** adds `LlamafileEmbeddings` class implementation for generating embeddings using [llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models. Includes related unit tests and notebook showing example usage. * **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
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
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
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
Christophe Bornet	177f51c7bd	community: Use default load() implementation in doc loaders (#18385) ... Following https://github.com/langchain-ai/langchain/pull/18289	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
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
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
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
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
Erick Friis	eefb49680f	multiple[patch]: fix deprecation versions (#18349)	6 months ago
Jib	72bfc1d3db	mongodb[minor]: MongoDB Partner Package -- Porting MongoDBAtlasVectorSearch (#17652) ... This PR migrates the existing MongoDBAtlasVectorSearch abstraction from the `langchain_community` section to the partners package section of the codebase. - [x] Run the partner package script as advised in the partner-packages documentation. - [x] Add Unit Tests - [x] Migrate Integration Tests - [x] Refactor `MongoDBAtlasVectorStore` (autogenerated) to `MongoDBAtlasVectorSearch` - [x] ~Remove~ deprecate the old `langchain_community` VectorStore references. ## Additional Callouts - Implemented the `delete` method - Included any missing async function implementations - `amax_marginal_relevance_search_by_vector` - `adelete` - Added new Unit Tests that test for functionality of `MongoDBVectorSearch` methods - Removed [`del res[self._embedding_key]`](e0c81e1cb0/libs/community/langchain_community/vectorstores/mongodb_atlas.py (L218)) in `_similarity_search_with_score` function as it would make the `maximal_marginal_relevance` function fail otherwise. The `Document` needs to store the embedding key in metadata to work. Checklist: - [x] PR title: Please title your PR "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 - [x] Pass lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified to check that you're passing lint and testing. See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ - [x] Add tests and docs: If you're adding a new integration, please include 1. Existing tests supplied in docs/docs do not change. Updated docstrings for new functions like `delete` 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. (This already exists) If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17. --------- Co-authored-by: Steven Silvester <steven.silvester@ieee.org> Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Kai Kugler	df234fb171	community[patch]: Fixing embedchain document mapping (#18255) ... - **Description:** The current embedchain implementation seems to handle document metadata differently than done in the current implementation of langchain and a KeyError is thrown. I would love for someone else to test this... --------- Co-authored-by: KKUGLER <kai.kugler@mercedes-benz.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com> Co-authored-by: Deshraj Yadav <deshraj@gatech.edu>	6 months ago
Tomaz Bratanic	5999c4a240	Add support for parameters in neo4j retrieval query (#18310) ... Sometimes, you want to use various parameters in the retrieval query of Neo4j Vector to personalize/customize results. Before, when there were only predefined chains, it didn't really make sense. Now that it's all about custom chains and LCEL, it is worth adding since users can inject any params they wish at query time. Isn't prone to SQL injection-type attacks since we use parameters and not concatenating strings.	6 months ago
Virat Singh	cd926ac3dd	community: Add PolygonFinancials Tool (#18324) ... **Description:** In this PR, I am adding a `PolygonFinancials` tool, which can be used to get financials data for a given ticker. The financials data is the fundamental data that is found in income statements, balance sheets, and cash flow statements of public US companies. **Twitter**: [@virattt](https://twitter.com/virattt)	6 months ago
Christophe Bornet	8a81fcd5d3	community: Fix deprecation version of AstraDB VectorStore (#17991)	6 months ago
mackong	2c42f3a955	ollama[patch]: delete suffix slash to avoid redirect (#18260) ... - **Description:** see [ollama](https://github.com/ollama/ollama/blob/main/server/routes.go#L949)'s route definitions - **Issue:** N/A - **Dependencies:** N/A	6 months ago
William De Vena	6b58943917	community[patch]: Invoke callback prior to yielding token (#18288) ... ## PR title community[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
Eugene Yurtsev	cd52433ba0	community[minor]: Add `SQLDatabaseLoader` document loader (#18281) ... - **Description:** A generic document loader adapter for SQLAlchemy on top of LangChain's `SQLDatabaseLoader`. - **Needed by:** https://github.com/crate-workbench/langchain/pull/1 - **Depends on:** GH-16655 - **Addressed to:** @baskaryan, @cbornet, @eyurtsev Hi from CrateDB again, in the same spirit like GH-16243 and GH-16244, this patch breaks out another commit from https://github.com/crate-workbench/langchain/pull/1, in order to reduce the size of this patch before submitting it, and to separate concerns. To accompany the SQLAlchemy adapter implementation, the patch includes integration tests for both SQLite and PostgreSQL. Let me know if corresponding utility resources should be added at different spots. With kind regards, Andreas. ### Software Tests ```console docker compose --file libs/community/tests/integration_tests/document_loaders/docker-compose/postgresql.yml up ``` ```console cd libs/community pip install psycopg2-binary pytest -vvv tests/integration_tests -k sqldatabase ``` ``` 14 passed ```  --------- Co-authored-by: Andreas Motl <andreas.motl@crate.io>	6 months ago
David Ruan	af35e2525a	community[minor]: add hugging_face_model document loader (#17323) ... - **Description:** add hugging_face_model document loader, - **Issue:** NA, - **Dependencies:** NA, --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>	6 months ago
Sanjaypranav V M	b9a495e56e	community[patch]: added latin-1 decoder to gmail search tool (#18116) ... some mails from flipkart , amazon are encoded with other plain text format so to handle UnicodeDecode error , added exception and latin decoder Thank you for contributing to LangChain! @hwchase17	6 months ago
Ashley Xu	e3211c2b3d	community[patch]: BigQueryVectorSearch JSON type unsupported for metadatas (#18234)	6 months ago
Ayo Ayibiowu	ac1d7d9de8	community[feat]: Adds LLMLingua as a document compressor (#17711) ... **Description**: This PR adds support for using the [LLMLingua project ](https://github.com/microsoft/LLMLingua) especially the LongLLMLingua (Enhancing Large Language Model Inference via Prompt Compression) as a document compressor / transformer. The LLMLingua project is an interesting project that can greatly improve RAG system by compressing prompts and contexts while keeping their semantic relevance. **Issue**: https://github.com/microsoft/LLMLingua/issues/31 **Dependencies**: [llmlingua](https://pypi.org/project/llmlingua/) @baskaryan --------- Co-authored-by: Ayodeji Ayibiowu <ayodeji.ayibiowu@getinge.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	6 months ago
Jaskirat Singh	ce682f5a09	community: vectorstores.kdbai - Added support for when no docs are present (#18103) ... - **Description:** By default it expects a list but that's not the case in corner scenarios when there is no document ingested(use case: Bootstrap application). \ Hence added as check, if the instance is panda Dataframe instead of list then it will procced with return immediately. - **Issue:** NA - **Dependencies:** NA - **Twitter handle:** jaskiratsingh1 --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	7 months ago
am-kinetica	9b8f6455b1	Langchain vectorstore integration with Kinetica (#18102) ... - **Description:** New vectorstore integration with the Kinetica database - **Issue:** - **Dependencies:** the Kinetica Python API `pip install gpudb==7.2.0.1`, - **Tag maintainer:** @baskaryan, @hwchase17 - **Twitter handle:** --------- Co-authored-by: Chad Juliano <cjuliano@kinetica.com>	7 months ago