Nodes

from fibonacci import LLMNode

node = LLMNode(
    id="analyze",                    # Unique identifier (required)
    name="Analyze Text",             # Human-readable name (required)
    instruction="Analyze: {{input.text}}"  # Prompt (required)
)

analyze = LLMNode(
    id="analyze_sentiment",
    name="Sentiment Analysis",
    instruction="""
    Analyze the sentiment of this text.
    Respond with: positive, negative, or neutral
    
    Text: {{input.text}}
    """,
    model="claude-sonnet-4-5-20250929",  # Model to use
    max_tokens=500,              # Max response tokens
    temperature=0.7,             # Creativity (0-1)
    dependencies=[]              # Nodes this depends on
)

LLMNode(
    id="summarize",
    instruction="""
    Summarize this data:
    
    Input: {{input.raw_data}}
    Previous analysis: {{analyze_sentiment}}
    User preferences: {{input.preferences.format}}
    """
)

from fibonacci import ToolNode

node = ToolNode(
    id="read_sheet",
    name="Read Google Sheet",
    tool="google_sheets_read",
    params={
        "spreadsheet_id": "{{input.sheet_id}}",
        "range": "A1:D100"
    }
)

send_email = ToolNode(
    id="send_report",
    name="Send Report Email",
    tool="gmail_send",
    params={
        "to": "{{input.recipient}}",
        "subject": "Weekly Report",
        "body": "{{generate_report}}"
    },
    timeout=30,              # Timeout in seconds
    dependencies=["generate_report"]
)

from fibonacci import list_tools, search_tools, print_tool_info

# List all tools
tools = list_tools()

# Search for specific tools
slack_tools = search_tools("slack")

# Get detailed info
print_tool_info("google_sheets_read")

from fibonacci import CriticNode

critic = CriticNode(
    id="evaluate_report",
    name="Evaluate Report Quality",
    target_node="generate_report",  # Node to evaluate
    criteria=["clarity", "completeness", "accuracy"]
)

result = wf.run(input_data={...})

evaluation = result.output_data["evaluate_report"]
# {
#   "score": 8.5,
#   "feedback": {
#     "clarity": "Well organized with clear sections",
#     "completeness": "Missing Q4 projections",
#     "accuracy": "All figures verified"
#   }
# }

critic = CriticNode(
    id="check_code",
    name="Code Review",
    target_node="generate_code",
    criteria=[
        "correctness",
        "efficiency", 
        "readability",
        "error_handling",
        "security"
    ]
)

from fibonacci import ConditionalNode

condition = ConditionalNode(
    id="check_sentiment",
    name="Check Sentiment",
    left_value="{{analyze_sentiment}}",
    operator="contains",
    right_value="negative",
    true_branch=["send_alert"],    # Nodes to run if true
    false_branch=["send_summary"]  # Nodes to run if false
)

# Check score and branch accordingly
check_score = ConditionalNode(
    id="check_score",
    name="Check Quality Score",
    left_value="{{evaluate_report.score}}",
    operator="greater_than",
    right_value="7",
    true_branch=["publish_report", "notify_team"],
    false_branch=["request_revision"]
)

# Node B depends on Node A
node_a = LLMNode(id="a", name="A", instruction="...")
node_b = LLMNode(id="b", name="B", instruction="...", dependencies=["a"])

# Or use fluent API
node_b = LLMNode(id="b", name="B", instruction="...").depends_on("a")

No dependencies    → Runs immediately
dependencies=["a"] → Waits for "a" to complete
dependencies=["a", "b"] → Waits for both "a" AND "b"

# Enable retries with fluent API
node = ToolNode(
    id="api_call",
    tool="http_request",
    params={...}
).with_retry(max_retries=3, delay=2.0)

# Or in constructor
node = ToolNode(
    id="api_call",
    tool="http_request",
    params={...},
    enable_retry=True,
    max_retries=3,
    retry_delay=2.0  # Seconds, with exponential backoff
)

# Only run if input.send_email is "true"
node = ToolNode(
    id="send",
    tool="gmail_send",
    params={...}
).with_condition(
    left_value="{{input.send_email}}",
    operator="equals",
    right_value="true"
)