id stringlengths 14 16 | text stringlengths 29 2.73k | source stringlengths 49 115 |
|---|---|---|
0fc1e61dbe7d-25 | {'action': 'on_llm_start', 'name': 'OpenAI', 'step': 7, 'starts': 5, 'ends': 2, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 1, 'llm_streams': 0, 'tool_starts': 2, 'tool_ends': 1, 'agent_ends': 0, 'prompts': 'Answer the following questions as best you can. You have access... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-26 | {'action': 'on_llm_end', 'token_usage_prompt_tokens': 242, 'token_usage_completion_tokens': 28, 'token_usage_total_tokens': 270, 'model_name': 'text-davinci-003', 'step': 8, 'starts': 5, 'ends': 3, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 2, 'llm_ends': 2, 'llm_streams': 0, 'tool_st... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-27 | I need to find out who Bryan Adams is married to.
Action: Search
Action Input: "Who is Bryan Adams married to"{'action': 'on_agent_action', 'tool': 'Search', 'tool_input': 'Who is Bryan Adams married to', 'log': ' I need to find out who Bryan Adams is married to.\nAction: Search\nAction Input: "Who is Bryan Adams marri... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-28 | Thought:{'action': 'on_tool_end', 'output': 'Bryan Adams has never married. In the 1990s, he was in a relationship with Danish model Cecilie Thomsen. In 2011, Bryan and Alicia Grimaldi, his ...', 'step': 11, 'starts': 7, 'ends': 4, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 2, 'llm_en... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-29 | {'action': 'on_llm_start', 'name': 'OpenAI', 'step': 12, 'starts': 8, 'ends': 4, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 3, 'llm_ends': 2, 'llm_streams': 0, 'tool_starts': 4, 'tool_ends': 2, 'agent_ends': 0, 'prompts': 'Answer the following questions as best you can. You have acces... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-30 | to the original input question\n\nBegin!\n\nQuestion: Who is the wife of the person who sang summer of 69?\nThought: I need to find out who sang summer of 69 and then find out who their wife is.\nAction: Search\nAction Input: "Who sang summer of 69"\nObservation: Bryan Adams - Summer Of 69 (Official Music Video).\nThou... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-31 | {'action': 'on_llm_end', 'token_usage_prompt_tokens': 314, 'token_usage_completion_tokens': 18, 'token_usage_total_tokens': 332, 'model_name': 'text-davinci-003', 'step': 13, 'starts': 8, 'ends': 5, 'errors': 0, 'text_ctr': 0, 'chain_starts': 1, 'chain_ends': 0, 'llm_starts': 3, 'llm_ends': 3, 'llm_streams': 0, 'tool_s... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-32 | I now know the final answer.
Final Answer: Bryan Adams has never been married.
{'action': 'on_agent_finish', 'output': 'Bryan Adams has never been married.', 'log': ' I now know the final answer.\nFinal Answer: Bryan Adams has never been married.', 'step': 14, 'starts': 8, 'ends': 6, 'errors': 0, 'text_ctr': 0, 'chain_... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-33 | 4 on_llm_start OpenAI 1 1 0 0 0
.. ... ... ... ... ... ... ...
66 on_tool_end NaN 11 7 4 0 0
67 on_llm_start OpenAI 12 8 4 0 0
68 on_llm_end NaN 13 8 ... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-34 | 69 1 0 3 ... NaN NaN NaN
70 1 1 3 ... NaN NaN NaN
tool tool_input log \
0 NaN NaN NaN
1 NaN ... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-35 | 0 2 Answer the following questions as best you can... OpenAI
1 7 Answer the following questions as best you can... OpenAI
2 12 Answer the following questions as best you can... OpenAI
output_step output \
0 3 I n... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
0fc1e61dbe7d-36 | 2 3rd and 4th grade 115.70 110.84 49.79
crawford gulpease_index osman
0 0.9 72.7 92.16
1 0.7 74.7 84.20
2 0.7 85.4 83.14
[3 rows x 24 columns]}
Could not update last created model in Task 988bd727b0e94a29a3ac0ee526813545... | https://python.langchain.com/en/latest/ecosystem/clearml_tracking.html |
5c7a50c19896-0 | .md
.pdf
Hugging Face
Contents
Installation and Setup
Wrappers
LLM
Embeddings
Tokenizer
Datasets
Hugging Face#
This page covers how to use the Hugging Face ecosystem (including the Hugging Face Hub) within LangChain.
It is broken into two parts: installation and setup, and then references to specific Hugging Face wra... | https://python.langchain.com/en/latest/ecosystem/huggingface.html |
5c7a50c19896-1 | from langchain.embeddings import HuggingFaceHubEmbeddings
For a more detailed walkthrough of this, see this notebook
Tokenizer#
There are several places you can use tokenizers available through the transformers package.
By default, it is used to count tokens for all LLMs.
You can also use it to count tokens when splitt... | https://python.langchain.com/en/latest/ecosystem/huggingface.html |
9b854f12f238-0 | .md
.pdf
Wolfram Alpha Wrapper
Contents
Installation and Setup
Wrappers
Utility
Tool
Wolfram Alpha Wrapper#
This page covers how to use the Wolfram Alpha API within LangChain.
It is broken into two parts: installation and setup, and then references to specific Wolfram Alpha wrappers.
Installation and Setup#
Install r... | https://python.langchain.com/en/latest/ecosystem/wolfram_alpha.html |
3e156585ff22-0 | .md
.pdf
AtlasDB
Contents
Installation and Setup
Wrappers
VectorStore
AtlasDB#
This page covers how to use Nomic’s Atlas ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Atlas wrappers.
Installation and Setup#
Install the Python package with pip install ... | https://python.langchain.com/en/latest/ecosystem/atlas.html |
cefe2fb6ad25-0 | .md
.pdf
GooseAI
Contents
Installation and Setup
Wrappers
LLM
GooseAI#
This page covers how to use the GooseAI ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific GooseAI wrappers.
Installation and Setup#
Install the Python SDK with pip install openai
Get y... | https://python.langchain.com/en/latest/ecosystem/gooseai.html |
f40b6094d334-0 | .md
.pdf
Llama.cpp
Contents
Installation and Setup
Wrappers
LLM
Embeddings
Llama.cpp#
This page covers how to use llama.cpp within LangChain.
It is broken into two parts: installation and setup, and then references to specific Llama-cpp wrappers.
Installation and Setup#
Install the Python package with pip install lla... | https://python.langchain.com/en/latest/ecosystem/llamacpp.html |
d130bdacb905-0 | .md
.pdf
Replicate
Contents
Installation and Setup
Calling a model
Replicate#
This page covers how to run models on Replicate within LangChain.
Installation and Setup#
Create a Replicate account. Get your API key and set it as an environment variable (REPLICATE_API_TOKEN)
Install the Replicate python client with pip ... | https://python.langchain.com/en/latest/ecosystem/replicate.html |
d130bdacb905-1 | And run it:
prompt = """
Answer the following yes/no question by reasoning step by step.
Can a dog drive a car?
"""
llm(prompt)
We can call any Replicate model (not just LLMs) using this syntax. For example, we can call Stable Diffusion:
text2image = Replicate(model="stability-ai/stable-diffusion:db21e45d3f7023abc2a46e... | https://python.langchain.com/en/latest/ecosystem/replicate.html |
4e0347a92ad2-0 | .md
.pdf
Metal
Contents
What is Metal?
Quick start
Metal#
This page covers how to use Metal within LangChain.
What is Metal?#
Metal is a managed retrieval & memory platform built for production. Easily index your data into Metal and run semantic search and retrieval on it.
Quick start#
Get started by creating a Meta... | https://python.langchain.com/en/latest/ecosystem/metal.html |
27aea657ecea-0 | .md
.pdf
RWKV-4
Contents
Installation and Setup
Usage
RWKV
Model File
Rwkv-4 models -> recommended VRAM
RWKV-4#
This page covers how to use the RWKV-4 wrapper within LangChain.
It is broken into two parts: installation and setup, and then usage with an example.
Installation and Setup#
Install the Python package with ... | https://python.langchain.com/en/latest/ecosystem/rwkv.html |
27aea657ecea-1 | RWKV VRAM
Model | 8bit | bf16/fp16 | fp32
14B | 16GB | 28GB | >50GB
7B | 8GB | 14GB | 28GB
3B | 2.8GB| 6GB | 12GB
1b5 | 1.3GB| 3GB | 6GB
See the rwkv pip page for more information about strategies, including streaming and cuda support.
previous
Runhouse
next
SearxNG Search API
Contents... | https://python.langchain.com/en/latest/ecosystem/rwkv.html |
26f1abd2f44d-0 | .md
.pdf
PromptLayer
Contents
Installation and Setup
Wrappers
LLM
PromptLayer#
This page covers how to use PromptLayer within LangChain.
It is broken into two parts: installation and setup, and then references to specific PromptLayer wrappers.
Installation and Setup#
If you want to work with PromptLayer:
Install the ... | https://python.langchain.com/en/latest/ecosystem/promptlayer.html |
26f1abd2f44d-1 | you can add pl_tags when instantializing to tag your requests on PromptLayer
you can add return_pl_id when instantializing to return a PromptLayer request id to use while tracking requests.
PromptLayer also provides native wrappers for PromptLayerChatOpenAI and PromptLayerOpenAIChat
previous
Prediction Guard
next
Qdran... | https://python.langchain.com/en/latest/ecosystem/promptlayer.html |
fb440b5fd67d-0 | .ipynb
.pdf
Aim
Aim#
Aim makes it super easy to visualize and debug LangChain executions. Aim tracks inputs and outputs of LLMs and tools, as well as actions of agents.
With Aim, you can easily debug and examine an individual execution:
Additionally, you have the option to compare multiple executions side by side:
Aim ... | https://python.langchain.com/en/latest/ecosystem/aim_tracking.html |
fb440b5fd67d-1 | aim_callback = AimCallbackHandler(
repo=".",
experiment_name="scenario 1: OpenAI LLM",
)
callbacks = [StdOutCallbackHandler(), aim_callback]
llm = OpenAI(temperature=0, callbacks=callbacks)
The flush_tracker function is used to record LangChain assets on Aim. By default, the session is reset rather than being t... | https://python.langchain.com/en/latest/ecosystem/aim_tracking.html |
fb440b5fd67d-2 | )
Scenario 3 The third scenario involves an agent with tools.
from langchain.agents import initialize_agent, load_tools
from langchain.agents import AgentType
# scenario 3 - Agent with Tools
tools = load_tools(["serpapi", "llm-math"], llm=llm, callbacks=callbacks)
agent = initialize_agent(
tools,
llm,
agent... | https://python.langchain.com/en/latest/ecosystem/aim_tracking.html |
fb440b5fd67d-3 | AnalyticDB
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/ecosystem/aim_tracking.html |
a64940054703-0 | .md
.pdf
Zilliz
Contents
Installation and Setup
Wrappers
VectorStore
Zilliz#
This page covers how to use the Zilliz Cloud ecosystem within LangChain.
Zilliz uses the Milvus integration.
It is broken into two parts: installation and setup, and then references to specific Milvus wrappers.
Installation and Setup#
Instal... | https://python.langchain.com/en/latest/ecosystem/zilliz.html |
ce971239ed45-0 | .md
.pdf
CerebriumAI
Contents
Installation and Setup
Wrappers
LLM
CerebriumAI#
This page covers how to use the CerebriumAI ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific CerebriumAI wrappers.
Installation and Setup#
Install with pip install cerebrium
G... | https://python.langchain.com/en/latest/ecosystem/cerebriumai.html |
aa08a6976ac6-0 | .md
.pdf
Hazy Research
Contents
Installation and Setup
Wrappers
LLM
Hazy Research#
This page covers how to use the Hazy Research ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Hazy Research wrappers.
Installation and Setup#
To use the manifest, install... | https://python.langchain.com/en/latest/ecosystem/hazy_research.html |
9b0bc929a5b9-0 | .ipynb
.pdf
Comet
Contents
Install Comet and Dependencies
Initialize Comet and Set your Credentials
Set OpenAI and SerpAPI credentials
Scenario 1: Using just an LLM
Scenario 2: Using an LLM in a Chain
Scenario 3: Using An Agent with Tools
Scenario 4: Using Custom Evaluation Metrics
Comet#
In this guide we will demons... | https://python.langchain.com/en/latest/ecosystem/comet_tracking.html |
9b0bc929a5b9-1 | llm = OpenAI(temperature=0.9, callbacks=callbacks, verbose=True)
llm_result = llm.generate(["Tell me a joke", "Tell me a poem", "Tell me a fact"] * 3)
print("LLM result", llm_result)
comet_callback.flush_tracker(llm, finish=True)
Scenario 2: Using an LLM in a Chain#
from langchain.callbacks import CometCallbackHandler,... | https://python.langchain.com/en/latest/ecosystem/comet_tracking.html |
9b0bc929a5b9-2 | project_name="comet-example-langchain",
complexity_metrics=True,
stream_logs=True,
tags=["agent"],
)
callbacks = [StdOutCallbackHandler(), comet_callback]
llm = OpenAI(temperature=0.9, callbacks=callbacks)
tools = load_tools(["serpapi", "llm-math"], llm=llm, callbacks=callbacks)
agent = initialize_agent(
... | https://python.langchain.com/en/latest/ecosystem/comet_tracking.html |
9b0bc929a5b9-3 | return {
"rougeLsum_score": results["rougeLsum"].fmeasure,
"reference": self.reference,
}
reference = """
The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building.
It was the first structure to reach a height of 300 metres.
It is now taller than the Chrysle... | https://python.langchain.com/en/latest/ecosystem/comet_tracking.html |
9b0bc929a5b9-4 | a title it held for 41 years until the Chrysler Building
in New York City was finished in 1930.
It was the first structure to reach a height of 300 metres.
Due to the addition of a broadcasting aerial at the top of the tower in 1957,
it is now taller t... | https://python.langchain.com/en/latest/ecosystem/comet_tracking.html |
ccb3149f6101-0 | .md
.pdf
MyScale
Contents
Introduction
Installation and Setup
Setting up envrionments
Wrappers
VectorStore
MyScale#
This page covers how to use MyScale vector database within LangChain.
It is broken into two parts: installation and setup, and then references to specific MyScale wrappers.
With MyScale, you can manage ... | https://python.langchain.com/en/latest/ecosystem/myscale.html |
ccb3149f6101-1 | index = MyScale(embedding_function, config)
index.add_documents(...)
Wrappers#
supported functions:
add_texts
add_documents
from_texts
from_documents
similarity_search
asimilarity_search
similarity_search_by_vector
asimilarity_search_by_vector
similarity_search_with_relevance_scores
VectorStore#
There exists a wrapper ... | https://python.langchain.com/en/latest/ecosystem/myscale.html |
a73d5c86dbc5-0 | .md
.pdf
LanceDB
Contents
Installation and Setup
Wrappers
VectorStore
LanceDB#
This page covers how to use LanceDB within LangChain.
It is broken into two parts: installation and setup, and then references to specific LanceDB wrappers.
Installation and Setup#
Install the Python SDK with pip install lancedb
Wrappers#
... | https://python.langchain.com/en/latest/ecosystem/lancedb.html |
2731e39eed5b-0 | .md
.pdf
Google Serper Wrapper
Contents
Setup
Wrappers
Utility
Output
Tool
Google Serper Wrapper#
This page covers how to use the Serper Google Search API within LangChain. Serper is a low-cost Google Search API that can be used to add answer box, knowledge graph, and organic results data from Google Search.
It is br... | https://python.langchain.com/en/latest/ecosystem/google_serper.html |
2731e39eed5b-1 | Yes.
Follow up: Who is the reigning men's U.S. Open champion?
Intermediate answer: Current champions Carlos Alcaraz, 2022 men's singles champion.
Follow up: Where is Carlos Alcaraz from?
Intermediate answer: El Palmar, Spain
So the final answer is: El Palmar, Spain
> Finished chain.
'El Palmar, Spain'
For a more detail... | https://python.langchain.com/en/latest/ecosystem/google_serper.html |
2d74d6478c8a-0 | .md
.pdf
Tair
Contents
Installation and Setup
Wrappers
VectorStore
Tair#
This page covers how to use the Tair ecosystem within LangChain.
Installation and Setup#
Install Tair Python SDK with pip install tair.
Wrappers#
VectorStore#
There exists a wrapper around TairVector, allowing you to use it as a vectorstore,
whe... | https://python.langchain.com/en/latest/ecosystem/tair.html |
8fbf035318e1-0 | .md
.pdf
Qdrant
Contents
Installation and Setup
Wrappers
VectorStore
Qdrant#
This page covers how to use the Qdrant ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Qdrant wrappers.
Installation and Setup#
Install the Python SDK with pip install qdrant-c... | https://python.langchain.com/en/latest/ecosystem/qdrant.html |
6cfc32aa065f-0 | .md
.pdf
DeepInfra
Contents
Installation and Setup
Wrappers
LLM
DeepInfra#
This page covers how to use the DeepInfra ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific DeepInfra wrappers.
Installation and Setup#
Get your DeepInfra api key from this link he... | https://python.langchain.com/en/latest/ecosystem/deepinfra.html |
275b084e9790-0 | .md
.pdf
AnalyticDB
Contents
VectorStore
AnalyticDB#
This page covers how to use the AnalyticDB ecosystem within LangChain.
VectorStore#
There exists a wrapper around AnalyticDB, allowing you to use it as a vectorstore,
whether for semantic search or example selection.
To import this vectorstore:
from langchain.vecto... | https://python.langchain.com/en/latest/ecosystem/analyticdb.html |
d6477a78b1bc-0 | .md
.pdf
OpenAI
Contents
Installation and Setup
Wrappers
LLM
Embeddings
Tokenizer
Moderation
OpenAI#
This page covers how to use the OpenAI ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific OpenAI wrappers.
Installation and Setup#
Install the Python SDK w... | https://python.langchain.com/en/latest/ecosystem/openai.html |
d6477a78b1bc-1 | Contents
Installation and Setup
Wrappers
LLM
Embeddings
Tokenizer
Moderation
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/ecosystem/openai.html |
f8fe94b9a57a-0 | .md
.pdf
AI21 Labs
Contents
Installation and Setup
Wrappers
LLM
AI21 Labs#
This page covers how to use the AI21 ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific AI21 wrappers.
Installation and Setup#
Get an AI21 api key and set it as an environment varia... | https://python.langchain.com/en/latest/ecosystem/ai21.html |
63732503b4c5-0 | .md
.pdf
Deep Lake
Contents
Why Deep Lake?
More Resources
Installation and Setup
Wrappers
VectorStore
Deep Lake#
This page covers how to use the Deep Lake ecosystem within LangChain.
Why Deep Lake?#
More than just a (multi-modal) vector store. You can later use the dataset to fine-tune your own LLM models.
Not only s... | https://python.langchain.com/en/latest/ecosystem/deeplake.html |
36abf52c9802-0 | .md
.pdf
Weaviate
Contents
Installation and Setup
Wrappers
VectorStore
Weaviate#
This page covers how to use the Weaviate ecosystem within LangChain.
What is Weaviate?
Weaviate in a nutshell:
Weaviate is an open-source database of the type vector search engine.
Weaviate allows you to store JSON documents in a class... | https://python.langchain.com/en/latest/ecosystem/weaviate.html |
36abf52c9802-1 | To import this vectorstore:
from langchain.vectorstores import Weaviate
For a more detailed walkthrough of the Weaviate wrapper, see this notebook
previous
Weights & Biases
next
Wolfram Alpha Wrapper
Contents
Installation and Setup
Wrappers
VectorStore
By Harrison Chase
© Copyright 2023, Harrison Chase.
... | https://python.langchain.com/en/latest/ecosystem/weaviate.html |
36c50832fe39-0 | .md
.pdf
Prediction Guard
Contents
Installation and Setup
LLM Wrapper
Example usage
Prediction Guard#
This page covers how to use the Prediction Guard ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Prediction Guard wrappers.
Installation and Setup#
Ins... | https://python.langchain.com/en/latest/ecosystem/predictionguard.html |
36c50832fe39-1 | llm_chain.predict(question=question)
previous
PipelineAI
next
PromptLayer
Contents
Installation and Setup
LLM Wrapper
Example usage
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/ecosystem/predictionguard.html |
534b2757e7eb-0 | .md
.pdf
OpenSearch
Contents
Installation and Setup
Wrappers
VectorStore
OpenSearch#
This page covers how to use the OpenSearch ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific OpenSearch wrappers.
Installation and Setup#
Install the Python package with ... | https://python.langchain.com/en/latest/ecosystem/opensearch.html |
c7b6013e2b53-0 | .md
.pdf
Google Search Wrapper
Contents
Installation and Setup
Wrappers
Utility
Tool
Google Search Wrapper#
This page covers how to use the Google Search API within LangChain.
It is broken into two parts: installation and setup, and then references to the specific Google Search wrapper.
Installation and Setup#
Instal... | https://python.langchain.com/en/latest/ecosystem/google_search.html |
71e3aed9f0d6-0 | .md
.pdf
Jina
Contents
Installation and Setup
Wrappers
Embeddings
Jina#
This page covers how to use the Jina ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Jina wrappers.
Installation and Setup#
Install the Python SDK with pip install jina
Get a Jina A... | https://python.langchain.com/en/latest/ecosystem/jina.html |
dd65867a3b55-0 | .md
.pdf
Yeager.ai
Contents
What is Yeager.ai?
yAgents
How to use?
Creating and Executing Tools with yAgents
Yeager.ai#
This page covers how to use Yeager.ai to generate LangChain tools and agents.
What is Yeager.ai?#
Yeager.ai is an ecosystem designed to simplify the process of creating AI agents and tools.
It featu... | https://python.langchain.com/en/latest/ecosystem/yeagerai.html |
dd65867a3b55-1 | create a tool that returns the n-th prime number
Load the tool into the toolkit: To load a tool into yAgents, simply provide a command to yAgents that says so. For example:
load the tool that you just created it into your toolkit
Execute the tool: To run a tool or agent, simply provide a command to yAgents that include... | https://python.langchain.com/en/latest/ecosystem/yeagerai.html |
2624326beeb9-0 | .md
.pdf
Graphsignal
Contents
Installation and Setup
Tracing and Monitoring
Graphsignal#
This page covers how to use Graphsignal to trace and monitor LangChain. Graphsignal enables full visibility into your application. It provides latency breakdowns by chains and tools, exceptions with full context, data monitoring,... | https://python.langchain.com/en/latest/ecosystem/graphsignal.html |
aef2b1b23ffc-0 | .md
.pdf
Redis
Contents
Installation and Setup
Wrappers
Cache
Standard Cache
Semantic Cache
VectorStore
Retriever
Memory
Vector Store Retriever Memory
Chat Message History Memory
Redis#
This page covers how to use the Redis ecosystem within LangChain.
It is broken into two parts: installation and setup, and then refe... | https://python.langchain.com/en/latest/ecosystem/redis.html |
aef2b1b23ffc-1 | To import this vectorstore:
from langchain.vectorstores import Redis
For a more detailed walkthrough of the Redis vectorstore wrapper, see this notebook.
Retriever#
The Redis vector store retriever wrapper generalizes the vectorstore class to perform low-latency document retrieval. To create the retriever, simply call ... | https://python.langchain.com/en/latest/ecosystem/redis.html |
f29edd57a935-0 | .ipynb
.pdf
Weights & Biases
Weights & Biases#
This notebook goes over how to track your LangChain experiments into one centralized Weights and Biases dashboard. To learn more about prompt engineering and the callback please refer to this Report which explains both alongside the resultant dashboards you can expect to s... | https://python.langchain.com/en/latest/ecosystem/wandb_tracking.html |
f29edd57a935-1 | visualize (bool): Whether to visualize the run.
complexity_metrics (bool): Whether to log complexity metrics.
stream_logs (bool): Whether to stream callback actions to W&B
Default values for WandbCallbackHandler(...)
visualize: bool = False,
complexity_metrics: bool = False,
stream_logs: bool = False,
NOTE: For... | https://python.langchain.com/en/latest/ecosystem/wandb_tracking.html |
f29edd57a935-2 | Tracking run with wandb version 0.14.0Run data is saved locally in /Users/harrisonchase/workplace/langchain/docs/ecosystem/wandb/run-20230318_150408-e47j1914Syncing run llm to Weights & Biases (docs) View project at https://wandb.ai/harrison-chase/langchain_callback_demo View run at https://wandb.ai/harrison-chase/lang... | https://python.langchain.com/en/latest/ecosystem/wandb_tracking.html |
f29edd57a935-3 | wandb_callback.flush_tracker(llm, name="simple_sequential")
Waiting for W&B process to finish... (success). View run llm at: https://wandb.ai/harrison-chase/langchain_callback_demo/runs/e47j1914Synced 5 W&B file(s), 2 media file(s), 5 artifact file(s) and 0 other file(s)Find logs at: ./wandb/run-20230318_150408-e47j191... | https://python.langchain.com/en/latest/ecosystem/wandb_tracking.html |
f29edd57a935-4 | ]
synopsis_chain.apply(test_prompts)
wandb_callback.flush_tracker(synopsis_chain, name="agent")
Waiting for W&B process to finish... (success). View run simple_sequential at: https://wandb.ai/harrison-chase/langchain_callback_demo/runs/jyxma7huSynced 4 W&B file(s), 2 media file(s), 6 artifact file(s) and 0 other file(s... | https://python.langchain.com/en/latest/ecosystem/wandb_tracking.html |
f29edd57a935-5 | Action: Search
Action Input: "Leo DiCaprio girlfriend"
Observation: DiCaprio had a steady girlfriend in Camila Morrone. He had been with the model turned actress for nearly five years, as they were first said to be dating at the end of 2017. And the now 26-year-old Morrone is no stranger to Hollywood.
Thought: I need t... | https://python.langchain.com/en/latest/ecosystem/wandb_tracking.html |
d4146ebfacd1-0 | .md
.pdf
SerpAPI
Contents
Installation and Setup
Wrappers
Utility
Tool
SerpAPI#
This page covers how to use the SerpAPI search APIs within LangChain.
It is broken into two parts: installation and setup, and then references to the specific SerpAPI wrapper.
Installation and Setup#
Install requirements with pip install ... | https://python.langchain.com/en/latest/ecosystem/serpapi.html |
92ba0b852fc6-0 | .md
.pdf
PipelineAI
Contents
Installation and Setup
Wrappers
LLM
PipelineAI#
This page covers how to use the PipelineAI ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific PipelineAI wrappers.
Installation and Setup#
Install with pip install pipeline-ai
Get... | https://python.langchain.com/en/latest/ecosystem/pipelineai.html |
d793f93d4eed-0 | .md
.pdf
Helicone
Contents
What is Helicone?
Quick start
How to enable Helicone caching
How to use Helicone custom properties
Helicone#
This page covers how to use the Helicone ecosystem within LangChain.
What is Helicone?#
Helicone is an open source observability platform that proxies your OpenAI traffic and provide... | https://python.langchain.com/en/latest/ecosystem/helicone.html |
d793f93d4eed-1 | Quick start
How to enable Helicone caching
How to use Helicone custom properties
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/ecosystem/helicone.html |
93013ac66d2a-0 | .md
.pdf
Milvus
Contents
Installation and Setup
Wrappers
VectorStore
Milvus#
This page covers how to use the Milvus ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Milvus wrappers.
Installation and Setup#
Install the Python SDK with pip install pymilvus... | https://python.langchain.com/en/latest/ecosystem/milvus.html |
9bc0b1ad8ad5-0 | .md
.pdf
GPT4All
Contents
Installation and Setup
Usage
GPT4All
Model File
GPT4All#
This page covers how to use the GPT4All wrapper within LangChain. The tutorial is divided into two parts: installation and setup, followed by usage with an example.
Installation and Setup#
Install the Python package with pip install py... | https://python.langchain.com/en/latest/ecosystem/gpt4all.html |
9bc0b1ad8ad5-1 | previous
GooseAI
next
Graphsignal
Contents
Installation and Setup
Usage
GPT4All
Model File
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/ecosystem/gpt4all.html |
0833a8f562c5-0 | .md
.pdf
StochasticAI
Contents
Installation and Setup
Wrappers
LLM
StochasticAI#
This page covers how to use the StochasticAI ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific StochasticAI wrappers.
Installation and Setup#
Install with pip install stochas... | https://python.langchain.com/en/latest/ecosystem/stochasticai.html |
9258ef80daf5-0 | .md
.pdf
SearxNG Search API
Contents
Installation and Setup
Self Hosted Instance:
Wrappers
Utility
Tool
SearxNG Search API#
This page covers how to use the SearxNG search API within LangChain.
It is broken into two parts: installation and setup, and then references to the specific SearxNG API wrapper.
Installation an... | https://python.langchain.com/en/latest/ecosystem/searx.html |
9258ef80daf5-1 | s.run("what is a large language model?")
Tool#
You can also load this wrapper as a Tool (to use with an Agent).
You can do this with:
from langchain.agents import load_tools
tools = load_tools(["searx-search"],
searx_host="http://localhost:8888",
engines=["github"])
Note that we ... | https://python.langchain.com/en/latest/ecosystem/searx.html |
deb0b75fe3d4-0 | .md
.pdf
Runhouse
Contents
Installation and Setup
Self-hosted LLMs
Self-hosted Embeddings
Runhouse#
This page covers how to use the Runhouse ecosystem within LangChain.
It is broken into three parts: installation and setup, LLMs, and Embeddings.
Installation and Setup#
Install the Python SDK with pip install runhouse... | https://python.langchain.com/en/latest/ecosystem/runhouse.html |
98a74deb0816-0 | .md
.pdf
Banana
Contents
Installation and Setup
Define your Banana Template
Build the Banana app
Wrappers
LLM
Banana#
This page covers how to use the Banana ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Banana wrappers.
Installation and Setup#
Install... | https://python.langchain.com/en/latest/ecosystem/bananadev.html |
98a74deb0816-1 | bad_words_ids=[[tokenizer.encode(' ', add_prefix_space=True)[0]]]
)
result = tokenizer.decode(output[0], skip_special_tokens=True)
# Return the results as a dictionary
result = {'output': result}
return result
You can find a full example of a Banana app here.
Wrappers#
LLM#
There exists an Banan... | https://python.langchain.com/en/latest/ecosystem/bananadev.html |
bb847ac258ce-0 | .md
.pdf
Unstructured
Contents
Installation and Setup
Wrappers
Data Loaders
Unstructured#
This page covers how to use the unstructured
ecosystem within LangChain. The unstructured package from
Unstructured.IO extracts clean text from raw source documents like
PDFs and Word documents.
This page is broken into two part... | https://python.langchain.com/en/latest/ecosystem/unstructured.html |
bb847ac258ce-1 | UnstructuredAPIFileIOLoader. That will process your document using the hosted Unstructured API.
Note that currently (as of 1 May 2023) the Unstructured API is open, but it will soon require
an API. The Unstructured documentation page will have
instructions on how to generate an API key once they’re available. Check out... | https://python.langchain.com/en/latest/ecosystem/unstructured.html |
8f819f9b1315-0 | .md
.pdf
Chroma
Contents
Installation and Setup
Wrappers
VectorStore
Chroma#
This page covers how to use the Chroma ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Chroma wrappers.
Installation and Setup#
Install the Python package with pip install chro... | https://python.langchain.com/en/latest/ecosystem/chroma.html |
38bdbd4e80c3-0 | .md
.pdf
Apify
Contents
Overview
Installation and Setup
Wrappers
Utility
Loader
Apify#
This page covers how to use Apify within LangChain.
Overview#
Apify is a cloud platform for web scraping and data extraction,
which provides an ecosystem of more than a thousand
ready-made apps called Actors for various scraping, c... | https://python.langchain.com/en/latest/ecosystem/apify.html |
3c81e89f5f81-0 | .md
.pdf
PGVector
Contents
Installation
Setup
Wrappers
VectorStore
Usage
PGVector#
This page covers how to use the Postgres PGVector ecosystem within LangChain
It is broken into two parts: installation and setup, and then references to specific PGVector wrappers.
Installation#
Install the Python package with pip inst... | https://python.langchain.com/en/latest/ecosystem/pgvector.html |
7b1fd0e431ae-0 | .md
.pdf
Databerry
Contents
What is Databerry?
Quick start
Databerry#
This page covers how to use the Databerry within LangChain.
What is Databerry?#
Databerry is an open source document retrievial platform that helps to connect your personal data with Large Language Models.
Quick start#
Retrieving documents stored i... | https://python.langchain.com/en/latest/ecosystem/databerry.html |
345198c2a111-0 | .rst
.pdf
Prompts
Prompts#
The reference guides here all relate to objects for working with Prompts.
PromptTemplates
Example Selector
Output Parsers
previous
How to serialize prompts
next
PromptTemplates
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/reference/prompts.html |
3931dd3eab87-0 | .rst
.pdf
Agents
Agents#
Reference guide for Agents and associated abstractions.
Agents
Tools
Agent Toolkits
previous
Memory
next
Agents
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/reference/agents.html |
ca1dab1ce4c0-0 | .rst
.pdf
Models
Models#
LangChain provides interfaces and integrations for a number of different types of models.
LLMs
Chat Models
Embeddings
previous
API References
next
Chat Models
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 02, 2023. | https://python.langchain.com/en/latest/reference/models.html |
1ccf7058e5a1-0 | .md
.pdf
Integrations
Integrations#
Besides the installation of this python package, you will also need to install packages and set environment variables depending on which chains you want to use.
Note: the reason these packages are not included in the dependencies by default is that as we imagine scaling this package,... | https://python.langchain.com/en/latest/reference/integrations.html |
1ccf7058e5a1-1 | PromptLayer:
Install requirements with pip install promptlayer (be sure to be on version 0.1.62 or higher)
Get an API key from promptlayer.com and set it using promptlayer.api_key=<API KEY>
SerpAPI:
Install requirements with pip install google-search-results
Get a SerpAPI api key and either set it as an environment var... | https://python.langchain.com/en/latest/reference/integrations.html |
1ccf7058e5a1-2 | OpenSearch:
Install requirements with pip install opensearch-py
If you want to set up OpenSearch on your local, here
DeepLake:
Install requirements with pip install deeplake
LlamaCpp:
Install requirements with pip install llama-cpp-python
Download model and convert following llama.cpp instructions
Milvus:
Install requi... | https://python.langchain.com/en/latest/reference/integrations.html |
e81be8e6f2eb-0 | .md
.pdf
Installation
Contents
Official Releases
Installing from source
Installation#
Official Releases#
LangChain is available on PyPi, so to it is easily installable with:
pip install langchain
That will install the bare minimum requirements of LangChain.
A lot of the value of LangChain comes when integrating it wi... | https://python.langchain.com/en/latest/reference/installation.html |
01c72ccf2345-0 | .rst
.pdf
Indexes
Indexes#
Indexes refer to ways to structure documents so that LLMs can best interact with them.
LangChain has a number of modules that help you load, structure, store, and retrieve documents.
Docstore
Text Splitter
Document Loaders
Vector Stores
Retrievers
Document Compressors
Document Transformers
pr... | https://python.langchain.com/en/latest/reference/indexes.html |
f879ad3027eb-0 | .rst
.pdf
Example Selector
Example Selector#
Logic for selecting examples to include in prompts.
pydantic model langchain.prompts.example_selector.LengthBasedExampleSelector[source]#
Select examples based on length.
Validators
calculate_example_text_lengths » example_text_lengths
field example_prompt: langchain.prompts... | https://python.langchain.com/en/latest/reference/modules/example_selector.html |
f879ad3027eb-1 | Create k-shot example selector using example list and embeddings.
Reshuffles examples dynamically based on query similarity.
Parameters
examples – List of examples to use in the prompt.
embeddings – An iniialized embedding API interface, e.g. OpenAIEmbeddings().
vectorstore_cls – A vector store DB interface class, e.g.... | https://python.langchain.com/en/latest/reference/modules/example_selector.html |
f879ad3027eb-2 | Create k-shot example selector using example list and embeddings.
Reshuffles examples dynamically based on query similarity.
Parameters
examples – List of examples to use in the prompt.
embeddings – An initialized embedding API interface, e.g. OpenAIEmbeddings().
vectorstore_cls – A vector store DB interface class, e.g... | https://python.langchain.com/en/latest/reference/modules/example_selector.html |
c9b7d85f6498-0 | .rst
.pdf
Memory
Memory#
pydantic model langchain.memory.ChatMessageHistory[source]#
field messages: List[langchain.schema.BaseMessage] = []#
add_ai_message(message: str) → None[source]#
Add an AI message to the store
add_user_message(message: str) → None[source]#
Add a user message to the store
clear() → None[source]#... | https://python.langchain.com/en/latest/reference/modules/memory.html |
c9b7d85f6498-1 | field human_prefix: str = 'Human'#
field k: int = 5#
load_memory_variables(inputs: Dict[str, Any]) → Dict[str, str][source]#
Return history buffer.
property buffer: List[langchain.schema.BaseMessage]#
String buffer of memory.
pydantic model langchain.memory.ConversationEntityMemory[source]#
Entity extractor & summarize... | https://python.langchain.com/en/latest/reference/modules/memory.html |
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