# Each conversation has a unique thread ID
thread_config = {"configurable": {"thread_id": "your-chat-id"}}

# Searches for similar golden examples
golden_examples = search_golden_examples_sync(
    query=latest_query,
    top_k=2,
    score_threshold=0.6
)

# Enhances the system prompt with examples
enhanced_content = build_prompt_with_golden_examples(
    base_prompt=SYSTEM_MESSAGE_PROMPT.content,
    golden_examples=golden_examples
)

set_llm_from_config(
    provider_type="anthropic",  # or "openai", "google", "custom"
    model_id="claude-3-5-sonnet-20241022",
    api_key="your-api-key",
    temperature=0.7
)

class AgentState(TypedDict):
    messages: Annotated[Sequence[BaseMessage], add_messages]
    title: Optional[str]
    session_id: Optional[str]
    user_id: Optional[str]
    langfuse_enabled: Optional[bool]
    generate_title: Optional[bool]

"Show me recent payment failures"
"What caused incident INC-2025-08-24-001?"
"Find Swift transfer issues from last week"

from src.copilot.graph import create_agent_graph

# Create the agent
agent_graph = create_agent_graph()

# Invoke with your query
result = agent_graph.invoke(
    input={"messages": [("user", "Find payment gateway errors")]},
    config={"configurable": {"thread_id": "session-123"}}
)

# Get the response
answer = result["messages"][-1].content

for mode, chunk in agent_graph.stream(
    input=inputs,
    config=thread_config,
    stream_mode=["custom", "messages"]
):
    if mode == "messages":
        token_chunk, metadata = chunk
        print(token_chunk.content, end="", flush=True)

DEFAULT_LLM_TEMPERATURE = 0.7  # Range: 0.0 (deterministic) to 1.0 (creative)

inputs = {
    "messages": [("user", query)],
    "langfuse_enabled": True,  # Enable tracing
    "session_id": session_id,
    "user_id": user_id
}