Chat APIs

Initiates a chat session with the specified ChatOps configuration and returns either a ChatResponse or an error message.

This function sends a request to the Ollama chat API with the given options.

Example:

let ops = defaultChatOps
result <- chat ops
case result of
  Left errorMsg -> putStrLn ("Error: " ++ errorMsg)
  Right response -> print response

To request a JSON format response:

let ops = defaultChatOps { format = Just JsonFormat }
result <- chat ops

To request a structured output with a JSON schema:

import Data.Aeson (object, (.=))
let ops = defaultChatOps { format = Just (SchemaFormat schema) }
result <- chat ops

chatJson is a higher level function that takes ChatOps (similar to chat) and also takes a Haskell type (that has To and From JSON instance) and returns the response in provided type.

This function simply calls chat with extra prompt appended to it, telling LLM to return the response in certain JSON format and serializes the response. This function will be helpful when you want to use the LLM to do something programmatic.

Note: This function predates the format parameter in the API. For new code, consider using the format parameter with a SchemaFormat instead, which leverages the model's native JSON output capabilities.

For Example: > let expectedJsonStrucutre = Example { > sortedList = ["sorted List here"] > , wasListAlreadSorted = False > } > let msg0 = Ollama.Message User "Sort given list: [4, 2 , 3, 67]. Also tell whether list was already sorted or not." Nothing > eRes3 <- > chatJson > defaultChatOps > { Chat.chatModelName = "llama3.2" > , Chat.messages = msg0 :| [] > } > expectedJsonStrucutre > (Just 2) > print eRes3 Output: > Example {sortedList = ["1","2","3","4"], wasListAlreadSorted = False}

Note: While Passing the type, construct the type that will help LLM understand the field better. For example, in the above example, the sortedList's value is written as "Sorted List here". This will help LLM understand context better.

You can also provide number of retries in case the LLM field to return the response in correct JSON in first attempt.

Represents a message within a chat, including its role and content.

Enumerated roles that can participate in a chat.

A default configuration for initiating a chat with a model. This can be used as a starting point and modified as needed.

Example:

let ops = defaultChatOps { chatModelName = "customModel" }
chat ops

E.g SchemaFormat { "type": "object", "properties": { "age": { "type": "integer" }, "available": { "type": "boolean" } }, "required": [ "age", "available" ] } |

Format specification for the chat output | Since 0.1.3.0

Helper function to create a JSON schema from a Haskell type