Chat Features in Julep

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Overview

Julep provides a robust chat system with various features for dynamic interaction with agents. Here’s an overview of the key components and functionalities.

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Features

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Input Structure

• Messages: An array of input messages representing the conversation so far.
• Tools: (Advanced) Additional tools provided for this specific interaction.
• Tool Choice: Specifies which tool the agent should use.
• Memory Access: Controls how the session accesses history and memories.(recall parameter)
• Additional Parameters: Various parameters to control the behavior of the chat. You can find more details in the Additional Parameters section.

Here’s an example of how a typical message object might be structured in a chat interaction:

  """
  Attributes for the Message object:
      role (Literal["user", "assistant", "system", "tool"]): The role of the message sender.
      tool_call_id (str | None): Optional identifier for a tool call associated with this message.
      content (Annotated[str | list[str] | list[Content | ContentModel7 | ContentModel] | None, Field(...)]): The main content of the message, which can be a string, a list of strings, or a list of content models.
      name (str | None): Optional name associated with the message.
      continue_ (Annotated[StrictBool | None, Field(alias="continue")]): Flag to indicate whether to continue the conversation without interruption.
      tool_calls (list[ChosenFunctionCall | ChosenComputer20241022 | ChosenTextEditor20241022 | ChosenBash20241022] | None): List of tool calls generated during the message creation, if any.
  """
  # Example of a simple message structure
  messages = [{"role": "user", "content": "Your query here"}]

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Additional Parameters

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Usage

Here’s an example of how to use the chat API in Julep using the SDKs:

# Create a session with custom recall options
client.sessions.create(
    agent=agent.id,
    user=user.id,
    recall=True,
    recall_options={
        "mode": "hybrid", # or "vector", "text"
        "num_search_messages": 4, # number of messages to search for documents
        "max_query_length": 1000, # maximum query length
        "alpha": 0.7, # weight to apply to BM25 vs Vector search results (ranges from 0 to 1)
        "confidence": 0.6, # confidence cutoff level (ranges from -1 to 1)
        "limit": 10, # limit of documents to return
        "lang": "en-US", # language to be used for text-only search
        "metadata_filter": {}, # metadata filter to apply to the search
        "mmr_strength": 0, # MMR Strength (ranges from 0 to 1)
    }
)

# Chat in the session
response = client.sessions.chat(
    session_id=session.id,
    messages=[
        {
            "role": "user",
            "content": "Tell me about Julep"
        }
    ],
    recall=True
)
print("Agent's response:", response.choices[0].message.content)
print("Searched Documents:", response.docs)

To learn more about the Session object, check out the Session page.

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Response

Both types of responses include the following fields:

• id: The unique identifier for the chat response
• choices: An object of generated message completions containing:
  • role: The role of the message (e.g. “assistant”, “user”, etc.)
  • id: Unique identifier for the message
  • content: list of actual message content
  • created_at: Timestamp when the message was created
  • name: Optional name associated with the message
  • tool_call_id: Optional ID referencing a tool call
  • tool_calls: Optional list of tool calls made during message generation
  • created_at: When this resource was created as UTC date-time
  • docs: List of document references used for this request, intended for citation purposes
  • jobs: List of UUIDs for background jobs that may have been initiated as a result of this interaction
  • usage: Statistics on token usage for the completion request

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Finish Reasons

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Support

If you need help with further questions in Julep:

• Join our Discord community
• Check the GitHub repository
• Contact support at hey@julep.ai