langchain

Commit Graph

Author	SHA1	Message	Date
Harrison Chase	0ca1641b14	release 0.0.117 (#1819 )	1 year ago
Harrison Chase	d5b4393bb2	Harrison/llm math (#1808 ) Co-authored-by: Vadym Barda <vadim.barda@gmail.com>	1 year ago
Bryan Helmig	7b6ff7fe00	Follow up to #1803 to remove dynamic docs route. (#1818 ) The base docs are going to be more stable and familiar for folks. Dynamic route is currently in flux.	1 year ago
Harrison Chase	76c7b1f677	Harrison/wandb (#1764 ) Co-authored-by: Anish Shah <93145909+ash0ts@users.noreply.github.com>	1 year ago
Paul	5aa8ece211	Corrected small typo in error message. (#1791 )	1 year ago
Harrison Chase	f6d24d5740	fix bug with openai token count (#1806 )	1 year ago
Harrison Chase	b1c4480d7c	fix typing (#1807 )	1 year ago
Daniel Chalef	b6ba989f2f	Add request timeout to ChatOpenAI (#1798 ) Add request_timeout field to ChatOpenAI. Defaults to 60s. --------- Co-authored-by: Daniel Chalef <daniel.chalef@private.org>	1 year ago
Ankush Gola	04acda55ec	Don't use dynamic api endpoint for Zapier NLA (#1803 ) From Robert "Right now the dynamic/ route for specifically the above endpoints is acting on all providers a user has set up, not just the provider for the supplied API key."	1 year ago
Harrison Chase	8e5c4ac867	bump version to 0.0.116 (#1788 )	1 year ago
Aratako	df8702fead	Small fix: Remove unused variable `summary_message_role` (#1789 ) After the changes in #1783, `summary_message_role` is no longer used in `ConversationSummaryBufferMemory`, so this PR removes it.	1 year ago
Harrison Chase	d5d50c39e6	Harrison/azure embeddings (#1787 ) Co-authored-by: Hemant <4627288+ghaccount@users.noreply.github.com>	1 year ago
Harrison Chase	1f18698b2a	Harrison/token buffer memory (#1786 ) Co-authored-by: Aratako <127325395+Aratako@users.noreply.github.com>	1 year ago
Harrison Chase	ef4945af6b	Harrison/chat token usage (#1785 )	1 year ago
Harrison Chase	7de2ada3ea	Harrison/add source column (#1784 ) Co-authored-by: Brian Graham <46691715+briangrahamww@users.noreply.github.com> Co-authored-by: briangrahamww <brian.graham@ww.com>	1 year ago
Bernat Felip i Díaz	262d4cb9a8	Use embedding instead of embedding function in ElasticVectorStore (#1692 ) While it might be a bit more restrictive, I find that using the Embedding interface as an input for the vector store creation is better than an embedding function because we can use bulk requests and possibly the retry logic if needed. I have seen that some vector store implementations use Embedding while others use embedding function so I don't know what is the criteria to have one or the other, in my opinion they should all just be Embedding or have a way more complex embedding function that accepts multiple texts instead of one by one. --------- Co-authored-by: Bernat Felip <bernat.felip@rea.ch>	1 year ago
Harrison Chase	951c158106	Harrison/summary message rol (#1783 ) Co-authored-by: Aratako <127325395+Aratako@users.noreply.github.com>	1 year ago
Bao Nguyen	85e4dd7fc3	Fix wrong prompt in refine chain (#1770 ) I got this during testing ``` ValueError: Missing some input keys: {'existing_answer'} ``` Upon review, the initial prompt should be `QUESTION_PROMPT_SELECTOR`. Co-authored-by: Bao Nguyen <bnguyen@roku.com>	1 year ago
Harrison Chase	b1b4a4065a	change chat default (#1782 ) Resolves https://github.com/hwchase17/langchain/issues/1532, resolves https://github.com/hwchase17/langchain/issues/1652.	1 year ago
Huang Chongdi	08f23c95d9	add encoding parameter to ObsidianLoader (#1752 )	1 year ago
hitoshi44	3cf493b089	Fix Document & Expose StringPromptTemplate as a custom-prompt-template. (#1753 ) Regarding [this issue](https://github.com/hwchase17/langchain/issues/1754), the code in the document [Creating a custom prompt template](https://langchain.readthedocs.io/en/latest/modules/prompts/examples/custom_prompt_template.html) is no longer functional and outdated. To address this, I have made the following changes: 1. Updated the guide in the document to use `StringPromptTemplate` instead of `BasePromptTemplate`. 2. Exposed `StringPromptTemplate` in `prompts/__init__.py` for easier importing.	1 year ago
hitoshi44	e635c86145	Slightly modified the docstring in `BasePromptTemplate` and `StringPromptTemplate`. (#1755 ) Regarding [this issue](https://github.com/hwchase17/langchain/issues/1754), `BasePromptTample` class docstring is a little outdated, thus it requires new method `format_prompt` for now. As such, I have made some modifications to the docstring to bring it up to date. I tried to adhere to the established document style, and would appreciate you for taking a look at this PR.	1 year ago
Harrison Chase	779790167e	Harrison/add warning to openaichat (#1781 )	1 year ago
Nils Durner	3161ced4bc	GPT-4 support (#1778 )	1 year ago
hung_ng__	3d6fcb85dc	Add load json prompt example (#1776 ) Hi, I just want to add a PR on the prompt serialization examples of loading from JSON so that it can contain the same as loading from YAML.	1 year ago
LeoGrin	3701b2901e	use namespace argument in Pinecone constructor (#1757 ) Fix #1756 Use the `namespace` argument of `Pinecone.from_exisiting_index` to set the default value of `namespace` for other methods. Leads to more expected behavior and easier integration in chains. For the test, I've added a line to delete and rebuild the `langchain-demo` index at the beginning of the test. I'm not 100% sure if it's a good idea but it makes the test reproducible.	1 year ago
Ben Gahtan	280cb4160d	Update tool.py (#1760 ) Fixed typo that said the Wikipedia tool was using Wolfram Alpha (instead of Wikipedia)	1 year ago
Kevin	80d8db5f60	Add service account support to Google Drive (#1761 ) Having service account support in the drive document loader would be nice. This is already present in the youtube loader. `cb646082ba/langchain/document_loaders/youtube.py (L76-L78)`	1 year ago
Piyush Jain	1a8790d808	Corrects copyright year (#1762 ) Corrected copyright year.	1 year ago
Eric Zhu	34840f3aee	AzureChatOpenAI for Azure Open AI's ChatGPT API (#1673 ) Add support for Azure OpenAI's ChatGPT API, which uses ChatML markups to format messages instead of objects. Related issues: #1591, #1659	1 year ago
Harrison Chase	8685d53adc	querying tabular data (#1758 )	1 year ago
Harrison Chase	2f6833d433	hotfix (#1742 )	1 year ago
Harrison Chase	dd90fd02d5	Harrison/move docs (#1741 )	1 year ago
Harrison Chase	07766a69f3	move docs (#1740 )	1 year ago
Harrison Chase	aa854988bf	bump version to 114 (#1739 )	1 year ago
Harrison Chase	96ebe98dc2	Harrison/latex splitter (#1738 ) Co-authored-by: Aidan Holland <thehappydinoa@gmail.com> Co-authored-by: Jan de Boer <44832123+Janldeboer@users.noreply.github.com>	1 year ago
Harrison Chase	45f05fc939	Harrison/blackboard loader (#1737 ) Co-authored-by: Aidan Holland <thehappydinoa@gmail.com>	1 year ago
Vincent Liao	cf9c3f54f7	docs: add docs link to agent toolkits (#1735 ) New to Langchain, was a bit confused where I should find the toolkits section when I'm at `agent/key_concepts` docs. I added a short link that points to the how to section.	1 year ago
Merbin J Anselm	fbc0c85b90	fix: agent json parser fails with text in suffix (#1734 ) While testing out `VectorDBQA` as a `Tool` for one of the conversation, I happened to get a response from LLM (OpenAI) like this <code> Could not parse LLM output: Here's a response using the Product Search tool: ```json { "action": "Product Search", "action_input": "pots for plants" } ``` This will allow you to search for pots for your plants and find a variety of options that are available for purchase. You can use this information to choose the pots that best fit your needs and preferences. </code> i.e. The response had a text before & after the expected JSON, leading to `JSONDecodeError`. It's fixed now, by removing text after '```' to remove unwanted text. The error I encountered in this Jupyter Notebook - [link](https://github.com/anselm94/chatbot-llm-ecommerce/blob/main/chatcommerce.ipynb) <details> <summary>Error encountered</summary> <code> --------------------------------------------------------------------------- JSONDecodeError Traceback (most recent call last) File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/agents/conversational_chat/base.py:104, in ConversationalChatAgent._extract_tool_and_input(self, llm_output) 103 try: --> 104 response = self.output_parser.parse(llm_output) 105 return response["action"], response["action_input"] File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/agents/conversational_chat/base.py:49, in AgentOutputParser.parse(self, text) 48 cleaned_output = cleaned_output.strip() ---> 49 response = json.loads(cleaned_output) 50 return {"action": response["action"], "action_input": response["action_input"]} File /opt/homebrew/Cellar/python@3.11/3.11.2_1/Frameworks/Python.framework/Versions/3.11/lib/python3.11/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/homebrew/Cellar/python@3.11/3.11.2_1/Frameworks/Python.framework/Versions/3.11/lib/python3.11/json/decoder.py:340, in JSONDecoder.decode(self, s, _w) 339 if end != len(s): --> 340 raise JSONDecodeError("Extra data", s, end) 341 return obj JSONDecodeError: Extra data: line 5 column 1 (char 74) During handling of the above exception, another exception occurred: ValueError Traceback (most recent call last) Cell In[22], line 1 ----> 1 ask_ai.run("Yes. I need pots for my plants") File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/chains/base.py:213, in Chain.run(self, args, kwargs) 211 if len(args) != 1: 212 raise ValueError("`run` supports only one positional argument.") --> 213 return self(args[0])[self.output_keys[0]] 215 if kwargs and not args: 216 return self(kwargs)[self.output_keys[0]] File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/chains/base.py:116, in Chain.__call__(self, inputs, return_only_outputs) 114 except (KeyboardInterrupt, Exception) as e: 115 self.callback_manager.on_chain_error(e, verbose=self.verbose) --> 116 raise e 117 self.callback_manager.on_chain_end(outputs, verbose=self.verbose) 118 return self.prep_outputs(inputs, outputs, return_only_outputs) File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/chains/base.py:113, in Chain.__call__(self, inputs, return_only_outputs) 107 self.callback_manager.on_chain_start( 108 {"name": self.__class__.__name__}, 109 inputs, 110 verbose=self.verbose, 111 ) 112 try: --> 113 outputs = self._call(inputs) 114 except (KeyboardInterrupt, Exception) as e: 115 self.callback_manager.on_chain_error(e, verbose=self.verbose) File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/agents/agent.py:499, in AgentExecutor._call(self, inputs) 497 # We now enter the agent loop (until it returns something). 498 while self._should_continue(iterations): --> 499 next_step_output = self._take_next_step( 500 name_to_tool_map, color_mapping, inputs, intermediate_steps 501 ) 502 if isinstance(next_step_output, AgentFinish): 503 return self._return(next_step_output, intermediate_steps) File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/agents/agent.py:409, in AgentExecutor._take_next_step(self, name_to_tool_map, color_mapping, inputs, intermediate_steps) 404 """Take a single step in the thought-action-observation loop. 405 406 Override this to take control of how the agent makes and acts on choices. 407 """ 408 # Call the LLM to see what to do. --> 409 output = self.agent.plan(intermediate_steps, inputs) 410 # If the tool chosen is the finishing tool, then we end and return. 411 if isinstance(output, AgentFinish): File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/agents/agent.py:105, in Agent.plan(self, intermediate_steps, kwargs) 94 """Given input, decided what to do. 95 96 Args: (...) 102 Action specifying what tool to use. 103 """ 104 full_inputs = self.get_full_inputs(intermediate_steps, kwargs) --> 105 action = self._get_next_action(full_inputs) 106 if action.tool == self.finish_tool_name: 107 return AgentFinish({"output": action.tool_input}, action.log) File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/agents/agent.py:67, in Agent._get_next_action(self, full_inputs) 65 def _get_next_action(self, full_inputs: Dict[str, str]) -> AgentAction: 66 full_output = self.llm_chain.predict(**full_inputs) ---> 67 parsed_output = self._extract_tool_and_input(full_output) 68 while parsed_output is None: 69 full_output = self._fix_text(full_output) File ~/Git/chatbot-llm-ecommerce/.venv/lib/python3.11/site-packages/langchain/agents/conversational_chat/base.py:107, in ConversationalChatAgent._extract_tool_and_input(self, llm_output) 105 return response["action"], response["action_input"] 106 except Exception: --> 107 raise ValueError(f"Could not parse LLM output: {llm_output}") ValueError: Could not parse LLM output: Here's a response using the Product Search tool: ```json { "action": "Product Search", "action_input": "pots for plants" } ``` This will allow you to search for pots for your plants and find a variety of options that are available for purchase. You can use this information to choose the pots that best fit your needs and preferences. </details>	1 year ago
Harrison Chase	276940fd9b	Harrison/official method (#1728 ) Co-authored-by: Aratako <127325395+Aratako@users.noreply.github.com>	1 year ago
Piyush Jain	cdff6c8181	Sagemaker Endpoint LLM (#1686 ) Updates #965 --------- Co-authored-by: Nimisha Mehta <116048415+nimimeht@users.noreply.github.com> Co-authored-by: Harrison Chase <harrisonchase@Harrisons-MBP.attlocal.net>	1 year ago
alekhyablue	cd45adbea2	adding new agent types in comments (#1711 )	1 year ago
Mario Kostelac	aff44d0a98	(OpenAI) Add model_name to LLMResult.llm_output (#1713 ) Given that different models have very different latencies and pricings, it's benefitial to pass the information about the model that generated the response. Such information allows implementing custom callback managers and track usage and price per model. Addresses https://github.com/hwchase17/langchain/issues/1557.	1 year ago
libra	8a95fdaee1	Fix all the bug in init Tool in docs (#1725 ) Fix all the example in the docs when init `Tool` Test by render with jupyter	1 year ago
Alexandros Mavrogiannis	5d8dc83ede	Bump duckdb-engine to 0.7.0 (#1726 ) Resolves https://github.com/hwchase17/langchain/issues/1272 Resolves https://github.com/hwchase17/langchain/issues/1578	1 year ago
Daniel Chalef	b157e0c1c3	Add HTML document_loader that includes page title metadata (#1720 ) This `BSHTMLLoader` document_loader loads an HTML document, extracts text and adds the page title to the returned Document's metadata. The loader uses the already installed bs4 package to extract both text content and the page title. Included in this PR is an example HTML file and an integration test that tests against this file. --------- Co-authored-by: Daniel Chalef <daniel.chalef@private.org>	1 year ago
Harrison Chase	40e9488055	fix async in agent (#1723 )	1 year ago
jerwelborn	55efbb8a7e	pydantic/json parsing (#1722 ) ``` class Joke(BaseModel): setup: str = Field(description="question to set up a joke") punchline: str = Field(description="answer to resolve the joke") joke_query = "Tell me a joke." # Or, an example with compound type fields. #class FloatArray(BaseModel): # values: List[float] = Field(description="list of floats") # #float_array_query = "Write out a few terms of fiboacci." model = OpenAI(model_name='text-davinci-003', temperature=0.0) parser = PydanticOutputParser(pydantic_object=Joke) prompt = PromptTemplate( template="Answer the user query.\n{format_instructions}\n{query}\n", input_variables=["query"], partial_variables={"format_instructions": parser.get_format_instructions()} ) _input = prompt.format_prompt(query=joke_query) print("Prompt:\n", _input.to_string()) output = model(_input.to_string()) print("Completion:\n", output) parsed_output = parser.parse(output) print("Parsed completion:\n", parsed_output) ``` ``` Prompt: Answer the user query. The output should be formatted as a JSON instance that conforms to the JSON schema below. For example, the object {"foo": ["bar", "baz"]} conforms to the schema {"foo": {"description": "a list of strings field", "type": "string"}}. Here is the output schema: --- {"setup": {"description": "question to set up a joke", "type": "string"}, "punchline": {"description": "answer to resolve the joke", "type": "string"}} --- Tell me a joke. Completion: {"setup": "Why don't scientists trust atoms?", "punchline": "Because they make up everything!"} Parsed completion: setup="Why don't scientists trust atoms?" punchline='Because they make up everything!' ``` Ofc, works only with LMs of sufficient capacity. DaVinci is reliable but not always. --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>	1 year ago
Alex Strick van Linschoten	d6bbf395af	Loosen PyYAML dependency (#1698 ) Hitting some dependency issues relating to this strict pinning. Unsure of the knock-on effects, but wanted to propose this loosening down a couple of versions.	1 year ago
Jonathan Pedoeem	606605925d	Adding ability to `return_pl_id` to all PromptLayer Models in LangChain (#1699 ) PromptLayer now has support for [several different tracking features.](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9) In order to use any of these features you need to have a request id associated with the request. In this PR we add a boolean argument called `return_pl_id` which will add `pl_request_id` to the `generation_info` dictionary associated with a generation. We also updated the relevant documentation.	1 year ago

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936 Commits (agent-lookup-tool-bad)

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