Chat Features in Julep

# 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)

# Chat with metadata for dynamic system prompts
response_with_metadata = client.sessions.chat(
    session_id=session.id,
    messages=[
        {
            "role": "user",
            "content": "Help me with Python"
        }
    ],
    metadata={
        "language": "Spanish",
        "expertise_level": "beginner",
        "custom_instructions": "Use simple examples"
    }
)
# The metadata will be available in the system template as {{metadata.language}}, etc.

# Chat with structured JSON response
response_json = client.sessions.chat(
    session_id=session.id,
    messages=[
        {
            "role": "user",
            "content": "Analyze the sentiment of: 'I love using Julep, it makes AI development so much easier!'"
        }
    ],
    response_format={"type": "json_object"},
    # When using response_format, instruct the model to return JSON
    settings={
        "temperature": 0.3
    }
)
# Response will be valid JSON that can be parsed
import json
sentiment_data = json.loads(response_json.choices[0].message.content)