langchain

Commit Graph

Author	SHA1	Message	Date
Mikelarg	dac2e0165a	community[minor]: Added GigaChat Embeddings support + updated previous GigaChat integration (#19516 ) - Description: Added integration with [GigaChat](https://developers.sber.ru/portal/products/gigachat) embeddings. Also added support for extra fields in GigaChat LLM and fixed docs.	5 months ago
billytrend-cohere	63343b4987	cohere[patch]: add cohere as a partner package (#19049 ) Description: adds support for langchain_cohere --------- Co-authored-by: Harry M <127103098+harry-cohere@users.noreply.github.com> Co-authored-by: Erick Friis <erick@langchain.dev>	5 months ago
Nikhil Kumar	3d3b46a782	docs: Update docs for `HuggingFacePipeline` (#19306 ) Updated `HuggingFacePipeline` docs to be in sync with list of supported tasks, including translation. - [x] PR title: "community: Update docs for `HuggingFacePipeline`" - 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: - Description: Update docs for `HuggingFacePipeline`, was earlier missing `translation` as a valid task - Issue: N/A - Dependencies: N/A - Twitter handle: None - [x] Add tests and docs: - [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/	5 months ago
aditya thomas	515aab3312	community[patch]: invoke callback prior to yielding token (openai) (#19389 ) Description: Invoke callback prior to yielding token for BaseOpenAI & OpenAIChat Issue: [Callback for on_llm_new_token should be invoked before the token is yielded by the model #16913](https://github.com/langchain-ai/langchain/issues/16913) Dependencies: None	5 months ago
aditya thomas	49e932cd24	community[patch]: invoke callback prior to yielding token (fireworks) (#19388 ) Description: Invoke callback prior to yielding token for Fireworks Issue: [Callback for on_llm_new_token should be invoked before the token is yielded by the model #16913](https://github.com/langchain-ai/langchain/issues/16913) Dependencies: None	5 months ago
aditya thomas	4856a87261	community[patch]: invoke callback prior to yielding token (llama.cpp) (#19392 ) Description: Invoke callback prior to yielding token for llama.cpp Issue: [Callback for on_llm_new_token should be invoked before the token is yielded by the model #16913](https://github.com/langchain-ai/langchain/issues/16913) Dependencies: None	5 months ago
Yudhajit Sinha	7d216ad1e1	community[patch]: Invoke callback prior to yielding token (titan_takeoff_pro) (#18624 ) ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream_ method in llms/titan_takeoff_pro. - Issue: #16913 - Dependencies: None	5 months ago
Yudhajit Sinha	455a74486b	community[patch]: Invoke callback prior to yielding token (sparkllm) (#18625 ) ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream_ method in llms/sparkllm. - Issue: #16913 - Dependencies: None	5 months ago
Yudhajit Sinha	5ac1860484	community[patch]: Invoke callback prior to yielding token (replicate) (#18626 ) ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream_ method in llms/replicate. - Issue: #16913 - Dependencies: None	5 months ago
Yudhajit Sinha	9525e392de	community[patch]: Invoke callback prior to yielding token (pai_eas_endpoint) (#18627 ) ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream_ method in llms/pai_eas_endpoint. - Issue: #16913 - Dependencies: None	5 months ago
Yudhajit Sinha	140f06e59a	community[patch]: Invoke callback prior to yielding token (openai) (#18628 ) ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream_ method in llms/openai. - Issue: #16913 - Dependencies: None	5 months ago
Yudhajit Sinha	280a914920	community[patch]: Invoke callback prior to yielding token (ollama) (#18629 ) ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream_ & _astream_ methods in llms/ollama. - Issue: #16913 - Dependencies: None	5 months ago
gonvee	b82644078e	community: Add `keep_alive` parameter to control how long the model w… (#19005 ) Add `keep_alive` parameter to control how long the model will stay loaded into memory with Ollama。 --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Taqi Jaffri	044bc22acc	Community: Add mistral oss model support to azureml endpoints, plus configurable timeout (#19123 ) - Description: There was no formatter for mistral models for Azure ML endpoints. Adding that, plus a configurable timeout (it was hard coded before) - Dependencies: none - Twitter handle: @tjaffri @docugami	5 months ago
Leonid Ganeline	7de1d9acfd	community: `llms` imports fixes (#18943 ) Classes are missed in __all__ and in different places of __init__.py - BaichuanLLM - ChatDatabricks - ChatMlflow - Llamafile - Mlflow - Together Added classes to __all__. I also sorted __all__ list. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	5 months ago
primate88	5aa68936e0	community: Fix import path for StreamingStdOutCallbackHandler example (#19170 ) - Description: - Updated the import path for `StreamingStdOutCallbackHandler` in the streaming response example within `huggingface_endpoint.py`. This change corrects the import statement to reflect the actual location of `StreamingStdOutCallbackHandler` in `langchain_core.callbacks.streaming_stdout`. - Issue: - None - Dependencies: - No additional dependencies are required for this change. - Twitter handle: - None ## Note: I have tested this change locally and confirmed that the `StreamingStdOutCallbackHandler` works as expected with the updated import path. This PR does not require the addition of new tests since it is a correction to documentation/examples rather than functional code.	5 months ago
Nikhil Kumar	635b3372bd	community[minor]: Add support for translation in HuggingFacePipeline (#19190 ) - [x] Support for translation: "community: Add support for translation in `HuggingFacePipeline`" - [x] Add support for translation in `HuggingFacePipeline`: - Description: Add support for translation in `HuggingFacePipeline`, which earlier used to support only text summarization and generation. - Issue: N/A - Dependencies: N/A - Twitter handle: None	5 months ago
Shuai Liu	c244e1a50b	community[patch]: Fixed bug in merging `generation_info` during chunk concatenation in Tongyi and ChatTongyi (#19014 ) - Description: In #16218 , during the `GenerationChunk` and `ChatGenerationChunk` concatenation, the `generation_info` merging changed from simple keys & values replacement to using the util method [`merge_dicts`](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/utils/_merge.py): ![image](https://github.com/langchain-ai/langchain/assets/2098020/10f315bf-7fe0-43a7-a0ce-6a3834b99a15) The `merge_dicts` method could not handle merging values of `int` or some other types, and would raise a [`TypeError`](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/utils/_merge.py#L55). This PR fixes this issue in the Tongyi and ChatTongyi Model by adopting the `generation_info` of the last chunk and discarding the `generation_info` of the intermediate chunks, ensuring that `stream` and `astream` function correctly. - Issue: - Related issues or PRs about Tongyi & ChatTongyi: #16605, #17105 - Other models or cases: #18441, #17376 - Dependencies: No new dependencies	5 months ago
case-k	ebc4a64f9e	docs: fix databricks document url (#19096 ) Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>	5 months ago
billytrend-cohere	7253b816cc	community: Add support for cohere SDK v5 (keeps v4 backwards compatibility) (#19084 ) - Description: Add support for cohere SDK v5 (keeps v4 backwards compatibility) --------- Co-authored-by: Erick Friis <erick@langchain.dev>	5 months ago
Anis ZAKARI	37e89ba5b1	community[patch]: Bedrock add support for mistral models (#18756 ) Description*: My previous [PR](https://github.com/langchain-ai/langchain/pull/18521) was mistakenly closed, so I am reopening this one. Context: AWS released two Mistral models on Bedrock last Friday (March 1, 2024). This PR includes some code adjustments to ensure their compatibility with the Bedrock class. --------- Co-authored-by: Anis ZAKARI <anis.zakari@hymaia.com> Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Phat Vo	3ecb903d49	community[patch] : Tidy up and update Clarifai SDK functions (#18314 ) Description : * Tidy up, add missing docstring and fix unused params * Enable using session token	6 months ago
Yunmo Koo	fee6f983ef	community[minor]: Integration for `Friendli` LLM and `ChatFriendli` ChatModel. (#17913 ) ## Description - Add [Friendli](https://friendli.ai/) integration for `Friendli` LLM and `ChatFriendli` chat model. - Unit tests and integration tests corresponding to this change are added. - Documentations corresponding to this change are added. ## Dependencies - Optional dependency [`friendli-client`](https://pypi.org/project/friendli-client/) package is added only for those who use `Frienldi` or `ChatFriendli` model. ## Twitter handle - https://twitter.com/friendliai	6 months ago
Erick Friis	1beb84b061	community[patch]: move pdf text tests to integration (#18746 )	6 months ago
Guangdong Liu	ced5e7bae7	community[patch]: Fix sparkllm authentication problem. (#18651 ) - Description: fix sparkllm authentication problem.The current timestamp is in RFC1123 format. The time deviation must be controlled within 300s. I changed to re-obtain the url every time I ask a question. https://www.xfyun.cn/doc/spark/general_url_authentication.html#_1-2-%E9%89%B4%E6%9D%83%E5%8F%82%E6%95%B0	6 months ago
Piyush Jain	2b234a4d96	Support for claude v3 models. (#18630 ) Fixes #18513. ## Description This PR attempts to fix the support for Anthropic Claude v3 models in BedrockChat LLM. The changes here has updated the payload to use the `messages` format instead of the formatted text prompt for all models; `messages` API is backwards compatible with all models in Anthropic, so this should not break the experience for any models. ## Notes The PR in the current form does not support the v3 models for the non-chat Bedrock LLM. This means, that with these changes, users won't be able to able to use the v3 models with the Bedrock LLM. I can open a separate PR to tackle this use-case, the intent here was to get this out quickly, so users can start using and test the chat LLM. The Bedrock LLM classes have also grown complex with a lot of conditions to support various providers and models, and is ripe for a refactor to make future changes more palatable. This refactor is likely to take longer, and requires more thorough testing from the community. Credit to PRs [18579](https://github.com/langchain-ai/langchain/pull/18579) and [18548](https://github.com/langchain-ai/langchain/pull/18548) for some of the code here. --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago
Eugene Yurtsev	4c25b49229	community[major]: breaking change in some APIs to force users to opt-in for pickling (#18696 ) This is a PR that adds a dangerous load parameter to force users to opt in to use pickle. This is a PR that's meant to raise user awareness that the pickling module is involved.	6 months ago
Liang Zhang	81985b31e6	community[patch]: Databricks SerDe uses cloudpickle instead of pickle (#18607 ) - Description: Databricks SerDe uses cloudpickle instead of pickle when serializing a user-defined function transform_input_fn since pickle does not support functions defined in `__main__`, and cloudpickle supports this. - Dependencies: cloudpickle>=2.0.0 Added a unit test.	6 months ago
Yudhajit Sinha	4570b477b9	community[patch]: Invoke callback prior to yielding token (titan_takeoff) (#18560 ) ## PR title community[patch]: Invoke callback prior to yielding token ## PR message - Description: Invoke callback prior to yielding token in _stream_ method in llms/titan_takeoff. - Issue: #16913 - Dependencies: None	6 months ago
Erick Friis	343438e872	community[patch]: deprecate community fireworks (#18544 )	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	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
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
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
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
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
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
Erick Friis	eefb49680f	multiple[patch]: fix deprecation versions (#18349 )	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
kYLe	17ecf6e119	community[patch]: Remove model limitation on Anyscale LLM (#17662 ) Description: Llama Guard is deprecated from Anyscale public endpoint. Issue: Change the default model. and remove the limitation of only use Llama Guard with Anyscale LLMs Anyscale LLM can also works with all other Chat model hosted on Anyscale. Also added `async_client` for Anyscale LLM	6 months ago
Erick Friis	29e0445490	community[patch]: BaseLLM typing in init (#18029 )	6 months ago
Guangdong Liu	4197efd67a	community: Fix SparkLLM error (#18015 ) 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" - Description: fix SparkLLM error - 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!	6 months ago
Brad Erickson	ecd72d26cf	community: Bugfix - correct Ollama API path to avoid HTTP 307 (#17895 ) Sets the correct /api/generate path, without ending /, to reduce HTTP requests. Reference: https://github.com/ollama/ollama/blob/efe040f8/docs/api.md#generate-request-streaming Before: DEBUG: Starting new HTTP connection (1): localhost:11434 DEBUG: http://localhost:11434 "POST /api/generate/ HTTP/1.1" 307 0 DEBUG: http://localhost:11434 "POST /api/generate HTTP/1.1" 200 None After: DEBUG: Starting new HTTP connection (1): localhost:11434 DEBUG: http://localhost:11434 "POST /api/generate HTTP/1.1" 200 None	6 months ago
Guangdong Liu	47b1b7092d	community[minor]: Add SparkLLM to community (#17702 )	6 months ago
Aymeric Roucher	0d294760e7	Community: Fuse HuggingFace Endpoint-related classes into one (#17254 ) ## Description Fuse HuggingFace Endpoint-related classes into one: - [HuggingFaceHub](`5ceaf784f3/libs/community/langchain_community/llms/huggingface_hub.py`) - [HuggingFaceTextGenInference](`5ceaf784f3/libs/community/langchain_community/llms/huggingface_text_gen_inference.py`) - and [HuggingFaceEndpoint](`5ceaf784f3/libs/community/langchain_community/llms/huggingface_endpoint.py`) Are fused into - HuggingFaceEndpoint ## Issue The deduplication of classes was creating a lack of clarity, and additional effort to develop classes leads to issues like [this hack](`5ceaf784f3/libs/community/langchain_community/llms/huggingface_endpoint.py (L159)`). ## Dependancies None, this removes dependancies. ## Twitter handle If you want to post about this: @AymericRoucher --------- Co-authored-by: Bagatur <baskaryan@gmail.com>	6 months ago
Mohammad Mohtashim	43dc5d3416	community[patch]: OpenLLM Client Fixes + Added Timeout Parameter (#17478 ) - OpenLLM was using outdated method to get the final text output from openllm client invocation which was raising the error. Therefore corrected that. - OpenLLM `_identifying_params` was getting the openllm's client configuration using outdated attributes which was raising error. - Updated the docstring for OpenLLM. - Added timeout parameter to be passed to underlying openllm client.	6 months ago
Mateusz Szewczyk	916332ef5b	ibm: added partners package `langchain_ibm`, added llm (#16512 ) - Description: Added `langchain_ibm` as an langchain partners package of IBM [watsonx.ai](https://www.ibm.com/products/watsonx-ai) LLM provider (`WatsonxLLM`) - Dependencies: [ibm-watsonx-ai](https://pypi.org/project/ibm-watsonx-ai/), - Tag maintainer: : --------- Co-authored-by: Erick Friis <erick@langchain.dev>	6 months ago

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