link updates

Author: jamescalam

learn/recommendation/onboarding-recommender/assets/onboarding_recommender_data_flow.jpg renamed to docs/assets/onboarding_recommender_data_flow.jpg

@@ -7,7 +7,7 @@
         "id": "SMFUgtvbFeLQ"
       },
       "source": [
-        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/generative-qa/openai/gen-qa-openai/gen-qa-openai.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/generation/generative-qa/openai/gen-qa-openai/gen-qa-openai.ipynb)"
+        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gen-qa-openai-fast.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/docs/gen-qa-openai-fast.ipynb)"
       ]
     },
     {
@@ -21,7 +21,7 @@
         "\n",
         "#### Fixing LLMs that Hallucinate\n",
         "\n",
-        "[![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/full-link.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/generative-qa/openai/gen-qa-openai/gen-qa-openai.ipynb)\n",
+        "[![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/full-link.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gen-qa-openai-fast.ipynb)\n",
         "\n",
         "In this notebook we will learn how to query relevant contexts to our queries from Pinecone, and pass these to a generative OpenAI model to generate an answer backed by real data sources. Required installs for this notebook are:"
       ]
@@ -80,7 +80,7 @@
         "\n",
         "There are many options for creating these dense vectors, like open source [sentence transformers](https://pinecone.io/learn/nlp/) or OpenAI's [ada-002 model](https://youtu.be/ocxq84ocYi0). We will use OpenAI's offering in this example.\n",
         "\n",
-        "We have already precomputed the embeddings here to speed things up. If you'd like to work through the full process however, check out [this notebook](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/generative-qa/openai/gen-qa-openai/gen-qa-openai.ipynb).\n",
+        "We have already precomputed the embeddings here to speed things up. If you'd like to work through the full process however, check out [this notebook](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gen-qa-openai-fast.ipynb).\n",
         "\n",
         "To download our precomputed embeddings we use Pinecone datasets:"
       ]

docs/gen-qa-openai-fast.ipynb

@@ -7,13 +7,13 @@
         "id": "GFLLl1Agum8O"
       },
       "source": [
-        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/gpt4-retrieval-augmentation/gpt-4-langchain-docs.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/generation/gpt4-retrieval-augmentation/gpt-4-langchain-docs.ipynb)\n",
+        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gpt-4-langchain-docs.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/docs/gpt-4-langchain-docs.ipynb)\n",
         "\n",
         "# GPT4 with Retrieval Augmentation over LangChain Docs\n",
         "\n",
         "In this notebook we'll work through an example of using GPT-4 with retrieval augmentation to answer questions about the LangChain Python library.\n",
         "\n",
-        "[![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/full-link.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/gpt4-retrieval-augmentation/gpt-4-langchain-docs.ipynb)\n",
+        "[![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/full-link.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/gpt-4-langchain-docs.ipynb)\n",
         "\n",
         "To begin we must install the prerequisite libraries:"
       ]

docs/gpt-4-langchain-docs.ipynb

@@ -7,7 +7,7 @@
         "id": "TXC2wBpCU9f7"
       },
       "source": [
-        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/langchain/handbook/08-langchain-retrieval-agent-fast.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/generation/langchain/handbook/08-langchain-retrieval-agent-fast.ipynb)"
+        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/08-langchain-retrieval-agent-fast.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/docs/08-langchain-retrieval-agent-fast.ipynb)"
       ]
     },
     {

docs/08-langchain-retrieval-agent-fast.ipynb renamed to docs/langchain-retrieval-agent.ipynb

@@ -7,7 +7,7 @@
         "id": "f0Qrii3fJYbS"
       },
       "source": [
-        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/langchain/handbook/05-langchain-retrieval-augmentation.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/generation/langchain/handbook/05-langchain-retrieval-augmentation.ipynb)"
+        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/langchain-retrieval-augmentation.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/docs/langchain-retrieval-augmentation.ipynb)"
       ]
     },
     {
@@ -27,7 +27,7 @@
         "\n",
         "A solution to this problem is *retrieval augmentation*. The idea behind this is that we retrieve relevant information from an external knowledge base and give that information to our LLM. In this notebook we will learn how to do that.\n",
         "\n",
-        "[![Open full notebook](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/full-link.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/langchain/handbook/05-langchain-retrieval-augmentation.ipynb)\n",
+        "[![Open full notebook](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/full-link.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/langchain-retrieval-augmentation.ipynb)\n",
         "\n",
         "To begin, we must install the prerequisite libraries that we will be using in this notebook."
       ]
@@ -69,7 +69,7 @@
       "source": [
         "## Building the Knowledge Base\n",
         "\n",
-        "We will download a pre-embedding dataset from `pinecone-datasets`. Allowing us to skip the embedding and preprocessing steps, if you'd rather work through those steps you can find the [full notebook here](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/langchain/handbook/05-langchain-retrieval-augmentation.ipynb)."
+        "We will download a pre-embedding dataset from `pinecone-datasets`. Allowing us to skip the embedding and preprocessing steps, if you'd rather work through those steps you can find the [full notebook here](https://colab.research.google.com/github/pinecone-io/examples/blob/master/docs/langchain-retrieval-augmentation.ipynb)."
       ]
     },
     {