Merge branch 'master' into template-readme-missing-env

templates/anthropic-iterative-search/README.md

@@ -1,3 +1,11 @@
 # anthropic-iterative-search
 
 Heavily inspired by [this notebook](https://github.com/anthropics/anthropic-cookbook/blob/main/long_context/wikipedia-search-cookbook.ipynb)
+
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+ANTHROPIC_API_KEY=<YOUR_ANTHROPIC_API_KEY
+```

templates/cassandra-entomology-rag/README.md

@@ -42,6 +42,14 @@ To put this to test, experiment with these example questions:
 "Do birds have wings?"                <-- no entomology here!
 ```
 
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```
+
 ## Reference
 
 Stand-alone repo with LangServe chain: [here](https://github.com/hemidactylus/langserve_cassandra_entomology_rag).

templates/cassandra-synonym-caching/README.md

@@ -13,7 +13,16 @@ You need:
 
 _Note:_ you can alternatively use a regular Cassandra cluster: to do so, make sure you provide the `USE_CASSANDRA_CLUSTER` entry as shown in `.env.template` and the subsequent environment variables to specify how to connect to it.
 
-You need to provide the connection parameters and secrets through environment variables. Please refer to `.env.template` for what variables are required.
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+ASTRA_DB_APPLICATION_TOKEN=<YOUR_ASTRA_DB_APPLICATION_TOKEN>
+ASTRA_DB_KEYSPACE=<YOUR_ASTRA_DB_KEYSPACE>
+ASTRA_DB_ID=<YOUR_ASTRA_DB_ID>
+```
 
 ## Reference
 

templates/csv-agent/README.md

@@ -3,3 +3,11 @@
 This is a csv agent that uses both a Python REPL as well as a vectorstore to allow for interaction with text data.
 
 Set up that is required is running `ingest.py` to do the ingestion into a vectorstore.
+
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/elastic-query-generator/README.md

@@ -22,6 +22,14 @@ With a deployment, update the connection string.
 
 Password and connection (elasticsearch url) can be found on the deployment console. Th 
 
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```
+
 ## Populating with data
 
 If you want to populate the DB with some example info, you can run `python ingest.py`.

templates/extraction-anthropic-functions/README.md

@@ -11,4 +11,12 @@ By default, it will extract the title and author of papers.
 
 This template will use `Claude2` by default. 
 
-Be sure that `ANTHROPIC_API_KEY` is set in your enviorment.
+Be sure that `ANTHROPIC_API_KEY` is set in your environment.
+
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+ANTHROPIC_API_KEY=<YOUR_ANTHROPIC_API_KEY>
+```

templates/extraction-openai-functions/README.md

@@ -10,4 +10,12 @@ By default, it will extract the title and author of papers.
 
 This template will use `OpenAI` by default. 
 
-Be sure that `OPENAI_API_KEY` is set in your environment.
+Be sure that `OPENAI_API_KEY` is set in your environment.
+
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/hyde/README.md

@@ -7,3 +7,11 @@ The idea behind this is that the hypothetical document may be closer in the embe
 For a more detailed description, read the full paper [here](https://arxiv.org/abs/2212.10496).
 
 For this example, we use a simple RAG architecture, although you can easily use this technique in other more complicated architectures.
+
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/llama2-functions/README.md

@@ -15,4 +15,12 @@ This template will use a `Replicate` [hosted version](https://replicate.com/andr
 
 Based on the `Replicate` example, the JSON schema is supplied directly in the prompt.
 
-Be sure that `REPLICATE_API_TOKEN` is set in your environment.
+Be sure that `REPLICATE_API_TOKEN` is set in your environment.
+
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+REPLICATE_API_TOKEN=<YOUR_REPLICATE_API_TOKEN>
+```

templates/openai-functions-agent/README.md

@@ -14,3 +14,12 @@ Be sure that `OPENAI_API_KEY` is set in your environment.
 This template will use `Tavily` by default. 
 
 Be sure that `TAVILY_API_KEY` is set in your environment.
+
+##  Environment variables
+
+You need to define the following environment variables
+
+```
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+TAVILY_API_KEY=<YOUR_TAVILY_API_KEY>
+```

templates/pirate-speak/README.md

@@ -7,3 +7,11 @@ This simple application converts user input into pirate speak
 This template will use `OpenAI` by default. 
 
 Be sure that `OPENAI_API_KEY` is set in your environment.
+
+##  Environment variables
+
+You need to define the following environment variable
+
+```
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/plate-chain/README.md

@@ -1 +1,9 @@
 # plate-chain
+
+##  Environment variables
+
+You need to define the following environment variable
+
+```
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/rag-aws-bedrock/README.md

@@ -18,10 +18,19 @@ You need to install the `faiss-cpu` package to work with the FAISS vector store.
 pip install faiss-cpu
 ```
 
-
 ##  LLM and Embeddings
 
 The code assumes that you are working with the `default` AWS profile and `us-east-1` region. If not, specify these environment variables to reflect the correct region and AWS profile.
 
 * `AWS_DEFAULT_REGION`
 * `AWS_PROFILE`
+
+
+## Environment variables
+
+You need (if not using default) to define the following environment variables
+
+```shell
+AWS_DEFAULT_REGION=<YOUR_AWS_DEFAULT_REGION>
+AWS_PROFILE=<YOUR_AWS_PROFILE>
+```

templates/rag-aws-kendra/README.md

@@ -15,7 +15,10 @@ You will need a Kendra Index setup before using this template. For setting up a
 
 The code assumes that you are working with the `default` AWS profile and `us-east-1` region. If not, specify these environment variables to reflect the correct region and AWS profile. 
 
-* `AWS_DEFAULT_REGION`
-* `AWS_PROFILE`
-
 This code also requires specifying the `KENDRA_INDEX_ID` env variable which should have the Index ID of the Kendra index. Note that the Index ID is a 36 character alphanumeric value that can be found in the index detail page.
+
+```shell
+AWS_DEFAULT_REGION=<YOUR_AWS_DEFAULT_REGION>
+AWS_PROFILE=<YOUR_AWS_PROFILE>
+KENDRA_INDEX_ID=<YOUR_KENDRA_INDEX_ID>
+```

templates/rag-chroma/README.md

@@ -13,3 +13,11 @@ These documents can be loaded from [many sources](https://python.langchain.com/d
 ##  LLM
 
 Be sure that `OPENAI_API_KEY` is set in order to the OpenAI models.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/rag-conversation/README.md

@@ -10,4 +10,15 @@ Be sure that `OPENAI_API_KEY` is set in order to use the OpenAI models.
 
 ##  Pinecone
 
-This template uses Pinecone as a vectorstore and requires that `PINECONE_API_KEY`, `PINECONE_ENVIRONMENT`, and `PINECONE_INDEX` are set.
+This template uses Pinecone as a vectorstore and requires that `PINECONE_API_KEY`, `PINECONE_ENVIRONMENT`, and `PINECONE_INDEX` are set.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+PINECONE_API_KEY=<YOUR_PINECONE_API_KEY>
+PINECONE_ENVIRONMENT=<YOUR_PINECONE_INDEX>
+PINECONE_INDEX=<YOUR_PINECONE_INDEX>
+```

templates/rag-elasticsearch/README.md

@@ -57,3 +57,14 @@ However, you can choose from a large number of document loaders [here](https://p
 # from inside your LangServe instance
 poe add rag-elasticsearch
 ```
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+ELASTIC_CLOUD_ID=<YOUR_ELASTIC_CLOUD_ID>
+ELASTIC_USERNAME=<YOUR_ELASTIC_USERNAME>
+ELASTIC_PASSWORD=<YOUR_ELASTIC_PASSWORD>
+ES_URL=http://localhost:9200
+```

templates/rag-fusion/README.md

@@ -3,3 +3,14 @@
 Re-implemented from [this GitHub repo](https://github.com/Raudaschl/rag-fusion), all credit to original author
 
 > RAG-Fusion, a search methodology that aims to bridge the gap between traditional search paradigms and the multifaceted dimensions of human queries. Inspired by the capabilities of Retrieval Augmented Generation (RAG), this project goes a step further by employing multiple query generation and Reciprocal Rank Fusion to re-rank search results.
+
+## Environment variables
+
+You need to define the following environment variable
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+PINECONE_API_KEY=<YOUR_PINECONE_API_KEY>
+PINECONE_ENVIRONMENT=<YOUR_PINECONE_INDEX>
+PINECONE_INDEX=<YOUR_PINECONE_INDEX>
+```

templates/rag-pinecone-multi-query/README.md

@@ -48,4 +48,15 @@ See `rag_pinecone_multi_query.ipynb` for example usage -
 from langserve.client import RemoteRunnable
 rag_app_pinecone = RemoteRunnable('http://0.0.0.0:8001/rag_pinecone_multi_query')
 rag_app_pinecone.invoke("What are the different types of agent memory")
-```
+```
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+PINECONE_API_KEY=<YOUR_PINECONE_API_KEY>
+PINECONE_ENVIRONMENT=<YOUR_PINECONE_INDEX>
+PINECONE_INDEX=<YOUR_PINECONE_INDEX>
+```

templates/rag-pinecone-rerank/README.md

@@ -12,7 +12,7 @@ Be sure that you have set a few env variables in `chain.py`:
 
 * `PINECONE_API_KEY`
 * `PINECONE_ENV`
-* `index_name`
+* `PINECONE_INDEX`
 
 ##  LLM
 
@@ -20,4 +20,17 @@ Be sure that `OPENAI_API_KEY` is set in order to the OpenAI models.
 
 ##  Cohere
 
-Be sure that `COHERE_API_KEY` is set in order to the ReRank endpoint.
+Be sure that `COHERE_API_KEY` is set in order to the ReRank endpoint.
+
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+COHERE_API_KEY=<YOUR_COHERE_API_KEY>
+PINECONE_API_KEY=<YOUR_PINECONE_API_KEY>
+PINECONE_ENVIRONMENT=<YOUR_PINECONE_INDEX>
+PINECONE_INDEX=<YOUR_PINECONE_INDEX>
+```

templates/rag-pinecone/README.md

@@ -10,8 +10,19 @@ Be sure that you have set a few env variables in `chain.py`:
 
 * `PINECONE_API_KEY`
 * `PINECONE_ENV`
-* `index_name`
+* `PINECONE_INDEX`
 
 ##  LLM
 
 Be sure that `OPENAI_API_KEY` is set in order to the OpenAI models.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+PINECONE_API_KEY=<YOUR_PINECONE_API_KEY>
+PINECONE_ENVIRONMENT=<YOUR_PINECONE_INDEX>
+PINECONE_INDEX=<YOUR_PINECONE_INDEX>
+```

templates/rag-redis/README.md

@@ -74,4 +74,17 @@ langchain serve add rag-redis
 Start the server:
 ```bash
 langchain start
-```
+```
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+REDIS_HOST=<YOUR_REDIS_HOST>
+REDIS_PORT=<YOUR_REDIS_PORT>
+REDIS_USER=<YOUR_REDIS_USER>
+REDIS_PASSWORD=<YOUR_REDIS_PASSWORD>
+INDEX_NAME=<YOUR_INDEX_NAME>
+```

templates/rag-semi-structured/README.md

@@ -44,4 +44,12 @@ Start server:
 langchain start
 ```
 
-See Jupyter notebook `rag_semi_structured` for various way to connect to the template.
+See Jupyter notebook `rag_semi_structured` for various way to connect to the template.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/rag-supabase/README.md

@@ -61,6 +61,9 @@ Use these steps to setup your Supabase database if you haven't already.
 
 Since we are using [`SupabaseVectorStore`](https://python.langchain.com/docs/integrations/vectorstores/supabase) and [`OpenAIEmbeddings`](https://python.langchain.com/docs/integrations/text_embedding/openai), we need to load their API keys.
 
+
+## Environment variables
+
 Create a `.env` file in the root of your project:
 
 _.env_

templates/rag-weaviate/README.md

@@ -13,4 +13,14 @@ Be sure that you have set a few env variables in `chain.py`:
 
 ##  LLM
 
-Be sure that `OPENAI_API_KEY` is set in order to the OpenAI models.
+Be sure that `OPENAI_API_KEY` is set in order to the OpenAI models.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+WEAVIATE_ENVIRONMENT=<YOUR_WEAVIATE_ENVIRONMENT>
+WEAVIATE_API_KEY=<YOUR_WEAVIATE_API_KEY>
+```

templates/rewrite-retrieve-read/README.md

@@ -5,3 +5,12 @@
 > Because the original query can not be always optimal to retrieve for the LLM, especially in the real world... we first prompt an LLM to rewrite the queries, then conduct retrieval-augmented reading
 
 We show how you can easily do that with LangChain Expression Language
+
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/self-query-supabase/README.md

@@ -61,6 +61,9 @@ Use these steps to setup your Supabase database if you haven't already.
 
 Since we are using [`SupabaseVectorStore`](https://python.langchain.com/docs/integrations/vectorstores/supabase) and [`OpenAIEmbeddings`](https://python.langchain.com/docs/integrations/text_embedding/openai), we need to load their API keys.
 
+
+## Environment variables
+
 Create a `.env` file in the root of your project:
 
 _.env_

templates/sql-llama2/README.md

@@ -18,4 +18,12 @@ You can see instructions to build this DB [here](https://github.com/facebookrese
 
 This template will use a `Replicate` [hosted version](https://replicate.com/meta/llama-2-13b-chat/versions/f4e2de70d66816a838a89eeeb621910adffb0dd0baba3976c96980970978018d) of LLaMA2. 
 
-Be sure that `REPLICATE_API_TOKEN` is set in your environment.
+Be sure that `REPLICATE_API_TOKEN` is set in your environment.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+REPLICATE_API_TOKEN=<YOUR_REPLICATE_API_TOKEN>
+```

templates/stepback-qa-prompting/README.md

@@ -7,3 +7,11 @@ Read the paper [here](https://arxiv.org/abs/2310.06117)
 See an excelent blog post on this by Cobus Greyling [here](https://cobusgreyling.medium.com/a-new-prompt-engineering-technique-has-been-introduced-called-step-back-prompting-b00e8954cacb)
 
 In this template we will replicate this technique. We modify the prompts used slightly to work better with chat models.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
+```

templates/summarize-anthropic/README.md

@@ -14,3 +14,11 @@ To do this, we can use various prompts from LangChain hub, such as:
 This template will use `Claude2` by default. 
 
 Be sure that `ANTHROPIC_API_KEY` is set in your enviorment.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+ANTHROPIC_API_KEY=<YOUR_ANTHROPIC_API_KEY>
+```

templates/xml-agent/README.md

@@ -15,3 +15,12 @@ Be sure that `ANTHROPIC_API_KEY` is set in your environment.
 This template will use `You.com` by default. 
 
 Be sure that `YDC_API_KEY` is set in your environment.
+
+## Environment variables
+
+You need to define the following environment variables
+
+```shell
+ANTHROPIC_API_KEY=<YOUR_ANTHROPIC_API_KEY>
+YDC_API_KEY=<YOUR_YDC_API_KEY>
+```