Adding Slugs to match old formatting

Adding Slugs to match old formatting for links being used on flier.

fern/docs/pages/models/details.mdx

@@ -1,6 +1,7 @@
 ---
 title: Model Options
 description: Reliable, future proof AI predictions
+slug: models/details
 ---
 
 Using Prediction Guard gives you quick and easy access to state-of-the-art LLMs, without you needing to spend weeks figuring out all of the implementation details, managing a bunch of different API specs, and setting up a secure infrastructure for model deployments.
@@ -22,9 +23,9 @@ Open access models are amazing these days! Each of these models was trained by a
 | Nous-Hermes-Llama2-13B       | Text Generation | Generating output in response to arbitrary instructions | [Alpaca](prompts#alpaca)           | 4096           | [link](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b)      |
 | Hermes-2-Pro-Mistral-7B      | Chat            | Instruction following or chat-like applications         | [ChatML](prompts#chatml)           | 4096           | [link](https://huggingface.co/NousResearch/Hermes-2-Pro-Mistral-7B)     |
 | Neural-Chat-7B               | Chat            | Instruction following or chat-like applications         | [Neural Chat](prompts#neural-chat) | 4096           | [link](https://huggingface.co/Intel/neural-chat-7b-v3-1)                |
-| Yi-34B-Chat                  | Chat            | Instruction following in English or Chinese             | [ChatML](prompts#chatml)           | 2048           | [link](https://huggingface.co/01-ai/Yi-34B-Chat)                        |               
+| Yi-34B-Chat                  | Chat            | Instruction following in English or Chinese             | [ChatML](prompts#chatml)           | 2048           | [link](https://huggingface.co/01-ai/Yi-34B-Chat)                        |
 | deepseek-coder-6.7b-instruct | Code Generation | Generating computer code or answering tech questions    | [Deepseek](prompts#deepseek)       | 4096           | [link](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct) |
-| sqlcoder-7b-2                | Code Generation | Generating SQL queries from natural language prompts    | [SQLCoder](prompts#sqlcoder)       | 4096           | [link](https://huggingface.co/defog/sqlcoder-7b-2)                      | 
+| sqlcoder-7b-2                | Code Generation | Generating SQL queries from natural language prompts    | [SQLCoder](prompts#sqlcoder)       | 4096           | [link](https://huggingface.co/defog/sqlcoder-7b-2)                      |
 
 ### Other models available
 

fern/docs/pages/usingllms/accessing.mdx

@@ -1,6 +1,7 @@
 ---
 title: Accessing LLMs
 description: Prediction Guard in action
+slug: usingllms/accessing
 ---
 
 (Run this example in Google Colab [here](https://drive.google.com/file/d/1H5YAkQKzCwG70eK9fRSBBngytHQvlPXZ/view?usp=sharing))

fern/docs/pages/usingllms/agents.mdx

@@ -1,6 +1,7 @@
 ---
 title: Agents
 description: Prediction Guard in action
+slug: usingllms/agents
 ---
 
 (Run this example in Google Colab [here](https://drive.google.com/file/d/1w_pDpWh-J9N3pUXAvI2QyIDT2N4W62Gf/view?usp=sharing))
@@ -42,7 +43,6 @@ agent.run("How are Domino's gift cards delivered?")
 
 This will verbosely log the agents activities until it reaching a final answer and generates the response:
 
-
 ```
 > Entering new AgentExecutor chain...
 We need to find information about Domino's gift card delivery process
@@ -54,4 +54,4 @@ Final Answer: Domino's gift cards can be delivered electronically or physically,
 
 > Finished chain.
 Domino's gift cards can be delivered electronically or physically, and can be used for online, phone, or in-store orders. They can be sent as eGift cards or physical cards, and can be used for both delivery and carryout orders.
-```
+```

fern/docs/pages/usingllms/augmentation.mdx

@@ -1,6 +1,7 @@
 ---
 title: Chaining and Retrieval
 description: Prediction Guard in action
+slug: usingllms/augmentation
 ---
 
 (Run this example in Google Colab [here](https://drive.google.com/file/d/1ukAPgQf39POwHhirIknTwKN7A9NLlFyt/view?usp=sharing))

fern/docs/pages/usingllms/chat.mdx

@@ -1,6 +1,7 @@
 ---
 title: Chat Completions
 description: Prediction Guard in action
+slug: usingllms/chat
 ---
 
 (Run this example in Google Colab [here](https://drive.google.com/file/d/15EBnc9aSC_KWeL677b_QHEOO7hIWDn1e/view?usp=sharing))
@@ -35,6 +36,7 @@ pg.Chat.list_models()
 ```
 
 To perform a chat completion, you need to create an array of `messages`. Each message object should have a:
+
 - `role` - "system", "user", or "assistant"
 - `content` - the text associated with the message
 
@@ -91,15 +93,15 @@ while True:
             "role": "user",
             "content": request
         })
-        
+
         response = pg.Chat.create(
             model="Neural-Chat-7B",
             messages=messages
         )['choices'][0]['message']['content'].split('\n')[0].strip()
-        
+
         messages.append({
             "role": "assistant",
             "content": response
         })
         print('Bot: ', response)
-```
+```

fern/fern.config.json

@@ -1,4 +1,4 @@
 {
   "organization": "Prediction-Guard",
-  "version": "0.19.11"
+  "version": "0.19.15"
 }