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Readme: Fix link to embeddings example and use python markup for code examples (#123)
* Fix URL to embeddings notebook * Specify python is used for the code block
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README.md
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README.md
@ -65,7 +65,7 @@ This project was largely inspired by a few projects seen on Twitter for which we
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To recreate this paper, use the following code snippet or checkout the [example notebook](https://github.com/hwchase17/langchain/blob/master/examples/self_ask_with_search.ipynb).
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```
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```python
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from langchain import SelfAskWithSearchChain, OpenAI, SerpAPIChain
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llm = OpenAI(temperature=0)
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@ -80,7 +80,7 @@ self_ask_with_search.run("What is the hometown of the reigning men's U.S. Open c
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To recreate this example, use the following code snippet or check out the [example notebook](https://github.com/hwchase17/langchain/blob/master/examples/llm_math.ipynb).
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```
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```python
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from langchain import OpenAI, LLMMathChain
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llm = OpenAI(temperature=0)
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@ -93,7 +93,7 @@ llm_math.run("How many of the integers between 0 and 99 inclusive are divisible
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You can also use this for simple prompting pipelines, as in the below example and this [example notebook](https://github.com/hwchase17/langchain/blob/master/examples/simple_prompts.ipynb).
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```
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```python
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from langchain import Prompt, OpenAI, LLMChain
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template = """Question: {question}
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@ -110,9 +110,9 @@ llm_chain.predict(question=question)
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**Embed & Search Documents**
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We support two vector databases to store and search embeddings -- FAISS and Elasticsearch. Here's a code snippet showing how to use FAISS to store embeddings and search for text similar to a query. Both database backends are featured in this [example notebook](https://github.com/hwchase17/langchain/blob/master/notebooks/examples/embeddings.ipynb).
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We support two vector databases to store and search embeddings -- FAISS and Elasticsearch. Here's a code snippet showing how to use FAISS to store embeddings and search for text similar to a query. Both database backends are featured in this [example notebook](https://github.com/hwchase17/langchain/blob/master/examples/embeddings.ipynb).
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```
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```python
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from langchain.embeddings.openai import OpenAIEmbeddings
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from langchain.faiss import FAISS
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from langchain.text_splitter import CharacterTextSplitter
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