id stringlengths 14 15 | text stringlengths 27 2.12k | source stringlengths 49 118 |
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6d6e5aa52026-0 | Math chain | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/llm_math |
6d6e5aa52026-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/llm_math |
6d6e5aa52026-2 | ** .3432")... Answer: 2.4116004626599237 > Finished chain. 'Answer: 2.4116004626599237'PreviousSelf-checking chainNextHTTP request chainCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/modules/chains/additional/llm_math |
206a6d711b8a-0 | Program-aided language model (PAL) chain | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/pal |
206a6d711b8a-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/pal |
206a6d711b8a-2 | > Entering new PALChain chain... def solution(): """Jan has three times the number of pets as Marcia. Marcia has two more pets than Cindy. If Cindy has four pets, how many total pets do the three have?""" cindy_pets = 4 marcia_pets = cindy_pets + 2 jan_pets = marcia_pets * 3 total_... | https://python.langchain.com/docs/modules/chains/additional/pal |
206a6d711b8a-3 | Count number of purple objects num_purple = len([object for object in objects if object[1] == 'purple']) answer = num_purple > Finished PALChain chain. '2'Intermediate Steps​You can also use the intermediate steps flag to return the code executed that generates the answer.pal_chain = PALChain.from_col... | https://python.langchain.com/docs/modules/chains/additional/pal |
206a6d711b8a-4 | += [('sunglasses', 'yellow')] * 2\n\n# Remove all pairs of sunglasses\nobjects = [object for object in objects if object[0] != 'sunglasses']\n\n# Count number of purple objects\nnum_purple = len([object for object in objects if object[1] == 'purple'])\nanswer = num_purple"PreviousOpenAPI calls with OpenAI functionsNext... | https://python.langchain.com/docs/modules/chains/additional/pal |
26005730e786-0 | Extraction | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/extraction |
26005730e786-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/extraction |
26005730e786-2 | UserWarning: A newer version of deeplake (3.6.4) is available. It's recommended that you update to the latest version using `pip install -U deeplake`. warnings.warn(llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613")Extracting entities​To extract entities, we need to create a schema where we specify all ... | https://python.langchain.com/docs/modules/chains/additional/extraction |
26005730e786-3 | to introduce a little hack - we will define our properties with an included entity type. Following we have an example where we also want to extract dog attributes from the passage. Notice the 'person' and 'dog' prefixes we use for each property; this tells the model which entity type the property refers to. In this way... | https://python.langchain.com/docs/modules/chains/additional/extraction |
26005730e786-4 | 'brunette'}]Unrelated entities​What if our entities are unrelated? In that case, the model will return the unrelated entities in different dictionaries, allowing us to successfully extract several unrelated entity types in the same call.Notice that we use required: []: we need to allow the model to return only person... | https://python.langchain.com/docs/modules/chains/additional/extraction |
26005730e786-5 | 'Milo', 'dog_breed': 'border collie'}]Extra info for an entity​What if.. we don't know what we want? More specifically, say we know a few properties we want to extract for a given entity but we also want to know if there's any extra information in the passage. Fortunately, we don't need to structure everything - we c... | https://python.langchain.com/docs/modules/chains/additional/extraction |
26005730e786-6 | {'dog_name': 'Willow', 'dog_breed': 'German Shepherd', 'dog_extra_information': 'likes to play with other dogs'}, {'dog_name': 'Milo', 'dog_breed': 'border collie', 'dog_extra_information': 'lives close by'}]Pydantic example​We can also use a Pydantic schema to choose the required properties a... | https://python.langchain.com/docs/modules/chains/additional/extraction |
26005730e786-7 | dog_name='Frosty'), Properties(person_name='Claudia', person_height=6, person_hair_color='brunette', dog_breed=None, dog_name=None)]PreviousElasticsearch databaseNextFLAREExtracting entitiesSeveral entity typesUnrelated entitiesExtra info for an entityPydantic exampleCommunityDiscordTwitterGitHubPythonJS/TSMoreHome... | https://python.langchain.com/docs/modules/chains/additional/extraction |
f40fdcddde81-0 | Neptune Open Cypher QA Chain | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/neptune_cypher_qa |
f40fdcddde81-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/neptune_cypher_qa |
f40fdcddde81-2 | many outgoing routes does the Austin airport have?")PreviousDynamically selecting from multiple retrieversNextRetrieval QA using OpenAI functionsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/modules/chains/additional/neptune_cypher_qa |
def6b663bc63-0 | Causal program-aided language (CPAL) chain | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-2 | Beth.""Bill buys the same number of pets as Obama.""Bob buys the same number of pets as Obama.""Ben buys the same number of pets as Obama.""Beth buys the same number of pets as Obama.""If Obama buys one pet, how many pets total does everyone buy?"into this.Outline of code examples demoed in this notebook.CPAL's value a... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-3 | The CPAL math expressions are modeling a chain of cause and effect relations, which can be intervened upon, whereas for the PAL chain math expressions are projected math identities.1.1 Complex narrative​Takeaway: PAL hallucinates, CPAL does not hallucinate.question = ( "Tim buys the same number of pets as Cindy an... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-4 | + obama_pets total_pets = tim_pets + cindy_pets + boris_pets result = total_pets return result > Finished chain. '5'cpal_chain.run(question) > Entering new chain... story outcome data name code value depends_on 0 obama ... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-5 | beth.value = obama.value 1.0 [obama] 5 cindy cindy.value = bill.value + bob.value 2.0 [bill, bob] 6 boris boris.value = ben.value + beth.value 2.0 [ben, beth] 7 tim tim.value = cindy.value + boris.value 4.0 [cindy, boris] query data { "question": "how man... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-6 | def solution(): """Jan has three times the number of pets as Marcia.Marcia has two more pets than Cindy.If Cindy has ten pets, how many pets does Barak have?""" cindy_pets = 10 marcia_pets = cindy_pets + 2 jan_pets = marcia_pets * 3 result = jan_pets return result > Fini... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-7 | "expression": "SELECT name, value FROM df WHERE name = 'barak'", "llm_error_msg": "" } unanswerable, query and outcome are incoherent outcome: name code value depends_on 0 cindy pass 10.0 [] 1 marcia marcia.value ... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-8 | three times the number of pets as Marcia. Marcia has two more pets than Cindy. If Cindy has four pets, how many total pets do the three have?""" cindy_pets = 4 marcia_pets = cindy_pets + 2 jan_pets = marcia_pets * 3 total_pets = cindy_pets + marcia_pets + jan_pets result = total_pets ... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-9 | "expression": "SELECT SUM(value) FROM df", "llm_error_msg": "" } > Finished chain. 28.0# wait 20 secs to see displaycpal_chain.draw(path="web.svg")SVG("web.svg")  Causal collider​question = ( "Jan has the number of pets as Marcia plus the number of p... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-10 | jan jan.value = marcia.value + cindy.value 4.0 [marcia, cindy] query data { "question": "how many total pets do the three have?", "expression": "SELECT SUM(value) FROM df", "llm_error_msg": "" } > Finished chain. 8.0# wait 20 secs to see displaycpal_chain.draw(path="... | https://python.langchain.com/docs/modules/chains/additional/cpal |
def6b663bc63-11 | [] 1 marcia marcia.value = cindy.value + 2 6.0 [cindy] 2 jan jan.value = cindy.value + marcia.value 10.0 [cindy, marcia] query data { "question": "how many total pets do the three have?", "expression": "SELECT SUM(value) FROM df", "llm_error_msg": "" ... | https://python.langchain.com/docs/modules/chains/additional/cpal |
5c135c2cbb8d-0 | Moderation | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/moderation |
5c135c2cbb8d-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/moderation |
5c135c2cbb8d-2 | moderation chain is harmful, there is not one best way to handle it, it probably depends on your application. Sometimes you may want to throw an error in the Chain (and have your application handle that). Other times, you may want to return something to the user explaining that the text was harmful. There could even be... | https://python.langchain.com/docs/modules/chains/additional/moderation |
5c135c2cbb8d-3 | *args, **kwargs) 136 if len(args) != 1: 137 raise ValueError("`run` supports only one positional argument.") --> 138 return self(args[0])[self.output_keys[0]] 140 if kwargs and not args: 141 return self(kwargs)[self.output_keys[0]] File ~/workplace/langchain/langcha... | https://python.langchain.com/docs/modules/chains/additional/moderation |
5c135c2cbb8d-4 | 82 return {self.output_key: output} File ~/workplace/langchain/langchain/chains/moderation.py:73, in OpenAIModerationChain._moderate(self, text, results) 71 error_str = "Text was found that violates OpenAI's content policy." 72 if self.error: ---> 73 raise ValueError(error_str) 74 else... | https://python.langchain.com/docs/modules/chains/additional/moderation |
5c135c2cbb8d-5 | abstraction.Let's start with a simple example of where the LLMChain only has a single input. For this purpose, we will prompt the model so it says something harmful.prompt = PromptTemplate(template="{text}", input_variables=["text"])llm_chain = LLMChain(llm=OpenAI(temperature=0, model_name="text-davinci-002"), prompt=p... | https://python.langchain.com/docs/modules/chains/additional/moderation |
5c135c2cbb8d-6 | = "sanitized_text"chain = SequentialChain(chains=[llm_chain, moderation_chain], input_variables=["setup", "new_input"])chain(inputs, return_only_outputs=True) {'sanitized_text': "Text was found that violates OpenAI's content policy."}PreviousLLM Symbolic MathNextDynamically selecting from multiple promptsCommunityDi... | https://python.langchain.com/docs/modules/chains/additional/moderation |
fc52e22e3537-0 | HTTP request chain | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/llm_requests |
fc52e22e3537-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/llm_requests |
fc52e22e3537-2 | input_variables=["query", "requests_result"], template=template,)chain = LLMRequestsChain(llm_chain=LLMChain(llm=OpenAI(temperature=0), prompt=PROMPT))question = "What are the Three (3) biggest countries, and their respective sizes?"inputs = { "query": question, "url": "https://www.google.com/search?q=" + ques... | https://python.langchain.com/docs/modules/chains/additional/llm_requests |
1150003fcab1-0 | Graph QA | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/graph_qa |
1150003fcab1-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/graph_qa |
1150003fcab1-2 | 'It won’t look like much, but if you stop and look closely, you’ll see a “Field of dreams,� the ground on which America’s future will be built. \nThis is where Intel, the American company that helped build Silicon Valley, is going to build its $20 billion semiconductor “mega site�. \nUp to eight state-of-... | https://python.langchain.com/docs/modules/chains/additional/graph_qa |
1150003fcab1-3 | Intel is helping build Silicon Valley > Finished chain. ' Intel is going to build a $20 billion semiconductor "mega site" with state-of-the-art factories, creating 10,000 new good-paying jobs and helping to build Silicon Valley.'Save the graph​We can also save and load the graph.graph.write_to_gml("graph.gm... | https://python.langchain.com/docs/modules/chains/additional/graph_qa |
78d5f8a7d205-0 | Tagging | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/tagging |
78d5f8a7d205-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/tagging |
78d5f8a7d205-2 | UserWarning: A newer version of deeplake (3.6.4) is available. It's recommended that you update to the latest version using `pip install -U deeplake`. warnings.warn(llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613")Simplest approach, only specifying type​We can start by specifying a few properties with ... | https://python.langchain.com/docs/modules/chains/additional/tagging |
78d5f8a7d205-3 | being smart about how we define our schema we can have more control over the model's output. Specifically we can define:possible values for each propertydescription to make sure that the model understands the propertyrequired properties to be returnedFollowing is an example of how we can use enum, description and requi... | https://python.langchain.com/docs/modules/chains/additional/tagging |
78d5f8a7d205-4 | con vos! Te voy a dar tu merecido!"chain.run(inp) {'sentiment': 'sad', 'aggressiveness': 10, 'language': 'spanish'}inp = "Weather is ok here, I can go outside without much more than a coat"chain.run(inp) {'sentiment': 'neutral', 'aggressiveness': 0, 'language': 'english'}Specifying schema with Pydantic​We can a... | https://python.langchain.com/docs/modules/chains/additional/tagging |
78d5f8a7d205-5 | vos! Te voy a dar tu merecido!"res = chain.run(inp)res Tags(sentiment='sad', aggressiveness=10, language='spanish')PreviousDocument QANextVector store-augmented text generationSimplest approach, only specifying typeMore controlSpecifying schema with PydanticCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCop... | https://python.langchain.com/docs/modules/chains/additional/tagging |
8b28790a9793-0 | Vector store-augmented text generation | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/vector_db_text_generation |
8b28790a9793-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/vector_db_text_generation |
8b28790a9793-2 | langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.vectorstores import Chromafrom langchain.text_splitter import CharacterTextSplitterfrom langchain.prompts import PromptTemplateimport pathlibimport subprocessimport tempfiledef get_github_docs(repo_owner, repo_name): with tempfile.TemporaryDirectory()... | https://python.langchain.com/docs/modules/chains/additional/vector_db_text_generation |
8b28790a9793-3 | yield Document(page_content=f.read(), metadata={"source": github_url})sources = get_github_docs("yirenlu92", "deno-manual-forked")source_chunks = []splitter = CharacterTextSplitter(separator=" ", chunk_size=1024, chunk_overlap=0)for source in sources: for chunk in splitter.split_text(source.page_content): sou... | https://python.langchain.com/docs/modules/chains/additional/vector_db_text_generation |
8b28790a9793-4 | as additional context in our simple LLM chain.def generate_blog_post(topic): docs = search_index.similarity_search(topic, k=4) inputs = [{"context": doc.page_content, "topic": topic} for doc in docs] print(chain.apply(inputs))generate_blog_post("environment variables") [{'text': '\n\nEnvironment variables a... | https://python.langchain.com/docs/modules/chains/additional/vector_db_text_generation |
8b28790a9793-5 | to the value `value`. This can be used to set any number of environment variables before running a command. For example, if we wanted to set the environment variable `VAR` to `hello` before running a Deno command, we could do so like this:\n\n```\nVAR=hello deno run main.ts\n```\n\nThis will set the environment variabl... | https://python.langchain.com/docs/modules/chains/additional/vector_db_text_generation |
8b28790a9793-6 | Subprocesses are powerful and can access system resources regardless of the permissions you granted to the Den'}, {'text': '\n\nEnvironment variables are an important part of any programming language, and Deno is no exception. Deno is a secure JavaScript and TypeScript runtime built on the V8 JavaScript engine, and it ... | https://python.langchain.com/docs/modules/chains/additional/vector_db_text_generation |
1a5c50fee6a8-0 | Analyze Document | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/analyze_document |
1a5c50fee6a8-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/analyze_document |
1a5c50fee6a8-2 | langchain.chains import AnalyzeDocumentChainsummarize_document_chain = AnalyzeDocumentChain(combine_docs_chain=summary_chain)summarize_document_chain.run(state_of_the_union) " In this speech, President Biden addresses the American people and the world, discussing the recent aggression of Russia's Vladimir Putin in U... | https://python.langchain.com/docs/modules/chains/additional/analyze_document |
df6f8cf2f7a8-0 | NebulaGraphQAChain | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/graph_nebula_qa |
df6f8cf2f7a8-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/graph_nebula_qa |
df6f8cf2f7a8-2 | create a new space%ngql CREATE SPACE IF NOT EXISTS langchain(partition_num=1, replica_factor=1, vid_type=fixed_string(128));# Wait for a few seconds for the space to be created.%ngql USE langchain;Create the schema, for full dataset, refer here.CREATE TAG IF NOT EXISTS movie(name string);CREATE TAG IF NOT EXISTS person... | https://python.langchain.com/docs/modules/chains/additional/graph_nebula_qa |
df6f8cf2f7a8-3 | the schema of database changes, you can refresh the schema information needed to generate nGQL statements.# graph.refresh_schema()print(graph.get_schema) Node properties: [{'tag': 'movie', 'properties': [('name', 'string')]}, {'tag': 'person', 'properties': [('name', 'string'), ('birthdate', 'string')]}] Edge pro... | https://python.langchain.com/docs/modules/chains/additional/graph_nebula_qa |
cac36929acf4-0 | FLARE | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-2 | Basically, the tokens that model is uncertain about are highlighted, and then an LLM is called to generate a question that would lead to that answer. For example, if the generated text is Joe Biden went to Harvard, and the tokens the model was uncertain about was Harvard, then a good generated question would be where d... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-3 | langchain.llms import OpenAIfrom langchain.schema import Documentfrom typing import Any, ListRetriever​class SerperSearchRetriever(BaseRetriever): search: GoogleSerperAPIWrapper = None def _get_relevant_documents( self, query: str, *, run_manager: CallbackManagerForRetrieverRun, **kwargs: Any ) -> Lis... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-4 | you should ground your answer in that context. Once you're done responding return FINISHED. >>> CONTEXT: >>> USER INPUT: explain in great detail the difference between the langchain framework and baby agi >>> RESPONSE: > Entering new QuestionGeneratorChain chain... Prompt after formatting: ... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-5 | a question to which the answer is the given term/entity/phrase: >>> USER INPUT: explain in great detail the difference between the langchain framework and baby agi >>> EXISTING PARTIAL RESPONSE: The Langchain Framework is a decentralized platform for natural language processing (NLP) applications. It use... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-6 | tools and services to help developers create and deploy NLP applications. Baby AGI, on the other hand, is an artificial general intelligence (AGI) platform. It uses a combination of deep learning and reinforcement learning to create an AI system that can learn and adapt to new tasks. Baby AGI is designed to be a... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-7 | Framework is a platform for NLP applications, while Baby AGI is an AI system designed for The question to which the answer is the term/entity/phrase " process data, allowing for secure and transparent data sharing." is: Prompt after formatting: Given a user input and an existing partial response as context... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-8 | the difference between the langchain framework and baby agi >>> EXISTING PARTIAL RESPONSE: The Langchain Framework is a decentralized platform for natural language processing (NLP) applications. It uses a blockchain-based distributed ledger to store and process data, allowing for secure and transparent data sha... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-9 | is an artificial general intelligence (AGI) platform. It uses a combination of deep learning and reinforcement learning to create an AI system that can learn and adapt to new tasks. Baby AGI is designed to be a general-purpose AI system that can be used for a variety of applications, including natural language processi... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-10 | to which the answer is the term/entity/phrase " NLP applications" is: > Finished chain. Generated Questions: ['What is the Langchain Framework?', 'What technology does the Langchain Framework use to store and process data for secure and transparent data sharing?', 'What technology does the Langchain Framework... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-11 | very general in nature, which means that while they can ... LangChain is an intuitive framework created to assist in developing applications driven by a language model, such as OpenAI or Hugging Face. LangChain is a software development framework designed to simplify the creation of applications using large language mo... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-12 | or Hugging Face. Missing: transparent | Must include:transparent. This technology keeps a distributed ledger on each blockchain node, making it more secure and transparent. The blockchain network can operate smart ... blockchain technology can offer a highly secured health data ledger to ... framework can be employed t... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-13 | simplifies embedding creation and storage using Pinecone and Chroma, with code that loads files, splits documents, and creates embedding ... Missing: technology | Must include:technology. Blockchain is one type of a distributed ledger. Distributed ledgers use independent computers (referred to as nodes) to recor... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-14 | such as OpenAI or Hugging Face. Missing: decentralized | Must include:decentralized. LangChain, created by Harrison Chase, is a Python library that provides out-of-the-box support to build NLP applications using LLMs. Missing: decentralized | Must include:decentralized. LangChain provides a standard interface for chain... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-15 | of the LangChain Python package covering models, prompts, chains, agents, indexes, and memory with OpenAI ... LangChain's collection of tools refers to a set of tools provided by the LangChain framework for developing applications powered by language models. LangChain is a framework for developing applications powered ... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-16 | explain in great detail the difference between the langchain framework and baby agi >>> RESPONSE: > Finished chain. > Finished chain. ' LangChain is a framework for developing applications powered by language models. It provides a standard interface for chains, lots of integrations with other tools... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-17 | is a more advanced AI system that can be used to create more complex applications.'flare.run("how are the origin stories of langchain and bitcoin similar or different?") > Entering new FlareChain chain... Current Response: Prompt after formatting: Respond to the user message using any relevant cont... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-18 | >>> USER INPUT: how are the origin stories of langchain and bitcoin similar or different? >>> EXISTING PARTIAL RESPONSE: Langchain and Bitcoin have very different origin stories. Bitcoin was created by the mysterious Satoshi Nakamoto in 2008 as a decentralized digital currency. Langchain, on the other hand,... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-19 | the purpose of creating Langchain?'] > Entering new _OpenAIResponseChain chain... Prompt after formatting: Respond to the user message using any relevant context. If context is provided, you should ground your answer in that context. Once you're done responding return FINISHED. >>> CONTEXT: Bitc... | https://python.langchain.com/docs/modules/chains/additional/flare |
cac36929acf4-20 | investing and trading is the regularity with which ... After all these giant leaps forward in the LLM space, OpenAI released ChatGPT — thrusting LLMs into the spotlight. LangChain appeared around the same time. Its creator, Harrison Chase, made the first commit in late October 2022. Leaving a short couple of m... | https://python.langchain.com/docs/modules/chains/additional/flare |
089ad6b802c4-0 | Dynamically selecting from multiple retrievers | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/multi_retrieval_qa_router |
089ad6b802c4-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/multi_retrieval_qa_router |
089ad6b802c4-2 | = TextLoader('../../state_of_the_union.txt').load_and_split()sou_retriever = FAISS.from_documents(sou_docs, OpenAIEmbeddings()).as_retriever()pg_docs = TextLoader('../../paul_graham_essay.txt').load_and_split()pg_retriever = FAISS.from_documents(pg_docs, OpenAIEmbeddings()).as_retriever()personal_texts = [ "I love a... | https://python.langchain.com/docs/modules/chains/additional/multi_retrieval_qa_router |
089ad6b802c4-3 | did the president say about the economy?")) > Entering new MultiRetrievalQAChain chain... state of the union: {'query': 'What did the president say about the economy in the 2023 State of the Union address?'} > Finished chain. The president said that the economy was stronger than it had been a year ... | https://python.langchain.com/docs/modules/chains/additional/multi_retrieval_qa_router |
089ad6b802c4-4 | through a project called ARPANET, which was funded by the United States Department of Defense. However, the World Wide Web, which is often confused with the Internet, was created in 1989 by British computer scientist Tim Berners-Lee.PreviousDynamically selecting from multiple promptsNextNeptune Open Cypher QA ChainComm... | https://python.langchain.com/docs/modules/chains/additional/multi_retrieval_qa_router |
659f8da64dad-0 | HugeGraph QA Chain | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/graph_hugegraph_qa |
659f8da64dad-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/graph_hugegraph_qa |
659f8da64dad-2 | You can run a local docker container by running the executing the following script:docker run \ --name=graph \ -itd \ -p 8080:8080 \ hugegraph/hugegraphIf we want to connect HugeGraph in the application, we need to install python sdk:pip3 install hugegraph-pythonIf you are using the docker container, you ne... | https://python.langchain.com/docs/modules/chains/additional/graph_hugegraph_qa |
659f8da64dad-3 | we can insert some data."""graph"""g = client.graph()g.addVertex("Person", {"name": "Al Pacino", "birthDate": "1940-04-25"})g.addVertex("Person", {"name": "Robert De Niro", "birthDate": "1943-08-17"})g.addVertex("Movie", {"name": "The Godfather"})g.addVertex("Movie", {"name": "The Godfather Part II"})g.addVertex("Movie... | https://python.langchain.com/docs/modules/chains/additional/graph_hugegraph_qa |
659f8da64dad-4 | statements.# graph.refresh_schema()print(graph.get_schema) Node properties: [name: Person, primary_keys: ['name'], properties: ['name', 'birthDate'], name: Movie, primary_keys: ['name'], properties: ['name']] Edge properties: [name: ActedIn, properties: []] Relationships: ['Person--ActedIn-->Movie'] Queryin... | https://python.langchain.com/docs/modules/chains/additional/graph_hugegraph_qa |
a22db2b26326-0 | Dynamically selecting from multiple prompts | 🦜�🔗 Langchain | https://python.langchain.com/docs/modules/chains/additional/multi_prompt_router |
a22db2b26326-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKGet startedIntroductionInstallationQuickstartModulesModel I/​OData connectionChainsHow toFoundationalDocumentsPopularAdditionalAnalyze DocumentSelf-critique chain with constitutional AICausal program-aided language (CPAL) cha... | https://python.langchain.com/docs/modules/chains/additional/multi_prompt_router |
a22db2b26326-2 | that you don't know.Here is a question:{input}"""math_template = """You are a very good mathematician. You are great at answering math questions. \You are so good because you are able to break down hard problems into their component parts, \answer the component parts, and then put them together to answer the broader qu... | https://python.langchain.com/docs/modules/chains/additional/multi_prompt_router |
a22db2b26326-3 | chain... math: {'input': 'What is the first prime number greater than 40 such that one plus the prime number is divisible by 3'} > Finished chain. ? The first prime number greater than 40 such that one plus the prime number is divisible by 3 is 43. To solve this problem, we can break down the question i... | https://python.langchain.com/docs/modules/chains/additional/multi_prompt_router |
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