How to power coding agents with Linkup

import requests
import json
from typing import Optional

class LinkupCodingAssistant:
    """Linkup integration for coding agents"""

    def __init__(self, api_key: str):
        self.api_key = api_key
        self.base_url = "https://api.linkup.so/v1/search"

    def _call_linkup(
        self,
        prompt: str,
        schema: dict,
        depth: str = "standard",
        include_domains: list = None,
        from_date: str = None
    ) -> dict:
        params = {
            "q": prompt,
            "depth": depth,
            "outputType": "structured",
            "structuredSchema": json.dumps(schema)
        }
        if include_domains:
            params["includeDomains"] = include_domains
        if from_date:
            params["fromDate"] = from_date

        response = requests.post(
            self.base_url,
            headers={"Authorization": f"Bearer {self.api_key}"},
            json=params
        )
        return response.json()

    def search_documentation(
        self,
        query: str,
        technology: str,
        version: Optional[str] = None
    ) -> dict:
        """Look up official documentation"""

        version_str = f"version {version}" if version else ""

        prompt = f"""
        Find official documentation for {technology} {version_str} related to: {query}

        Scrape the documentation page to extract:
        - Relevant section content
        - Code examples
        - Function signatures with parameters
        - Return types
        - Warnings or important notes

        Prioritize official documentation over tutorials.
        """

        schema = {
            "type": "object",
            "properties": {
                "source_url": {"type": "string"},
                "description": {"type": "string"},
                "code_examples": {
                    "type": "array",
                    "items": {
                        "type": "object",
                        "properties": {
                            "language": {"type": "string"},
                            "code": {"type": "string"}
                        }
                    }
                },
                "api_signatures": {
                    "type": "array",
                    "items": {
                        "type": "object",
                        "properties": {
                            "name": {"type": "string"},
                            "signature": {"type": "string"},
                            "parameters": {"type": "array"},
                            "return_type": {"type": "string"}
                        }
                    }
                },
                "warnings": {"type": "array", "items": {"type": "string"}}
            }
        }

        return self._call_linkup(
            prompt,
            schema,
            depth="deep"
        )

    def troubleshoot_error(
        self,
        error_message: str,
        technology: str,
        context: Optional[str] = None
    ) -> dict:
        """Find solutions for an error"""

        context_str = f"Context: {context}" if context else ""

        prompt = f"""
        Find solutions for this error in {technology}:

        Error: {error_message}
        {context_str}

        Search Stack Overflow and GitHub Issues.

        For each solution, extract:
        - Root cause
        - Fix with code changes
        - When this solution applies

        Rank by recency and community validation.
        """

        schema = {
            "type": "object",
            "properties": {
                "solutions": {
                    "type": "array",
                    "items": {
                        "type": "object",
                        "properties": {
                            "source_url": {"type": "string"},
                            "root_cause": {"type": "string"},
                            "solution": {"type": "string"},
                            "code_fix": {"type": "string"},
                            "confidence": {"type": "string"},
                            "upvotes": {"type": "integer"}
                        }
                    }
                },
                "recommended_solution": {"type": "integer"}
            }
        }

        return self._call_linkup(
            prompt,
            schema,
            depth="standard",
            include_domains=["stackoverflow.com", "github.com"]
        )

    def find_code_example(
        self,
        goal: str,
        language: str,
        framework: Optional[str] = None
    ) -> dict:
        """Find implementation examples"""

        framework_str = f"using {framework}" if framework else ""

        prompt = f"""
        Find code examples for: {goal}
        Language: {language} {framework_str}

        Search for:
        1. Official documentation examples
        2. Well-maintained GitHub repositories
        3. Highly-voted Stack Overflow answers

        Extract complete code with dependencies and setup steps.
        """

        schema = {
            "type": "object",
            "properties": {
                "examples": {
                    "type": "array",
                    "items": {
                        "type": "object",
                        "properties": {
                            "source_url": {"type": "string"},
                            "source_quality": {"type": "string"},
                            "dependencies": {"type": "array"},
                            "code": {"type": "string"},
                            "explanation": {"type": "string"}
                        }
                    }
                },
                "recommended_approach": {"type": "string"}
            }
        }

        return self._call_linkup(prompt, schema, depth="deep")

    def check_security(
        self,
        package: str,
        version: str,
        ecosystem: str
    ) -> dict:
        """Check for known vulnerabilities"""

        prompt = f"""
        Search for security vulnerabilities in {package} version {version} ({ecosystem}).

        Check:
        - CVE databases
        - GitHub Advisory Database
        - Package security advisories

        For each vulnerability, extract CVE ID, severity, affected versions, and fix.
        """

        schema = {
            "type": "object",
            "properties": {
                "vulnerabilities": {
                    "type": "array",
                    "items": {
                        "type": "object",
                        "properties": {
                            "cve_id": {"type": "string"},
                            "severity": {"type": "string"},
                            "cvss_score": {"type": "number"},
                            "affected_versions": {"type": "string"},
                            "fixed_version": {"type": "string"},
                            "description": {"type": "string"},
                            "mitigation": {"type": "string"}
                        }
                    }
                },
                "security_status": {"type": "string"},
                "recommended_action": {"type": "string"}
            }
        }

        return self._call_linkup(
            prompt,
            schema,
            depth="standard",
            include_domains=["nvd.nist.gov", "github.com/advisories", "snyk.io"]
        )

# Example usage
if __name__ == "__main__":
    assistant = LinkupCodingAssistant(api_key="your-api-key")

    # Documentation lookup
    docs = assistant.search_documentation(
        query="async context managers",
        technology="Python",
        version="3.11"
    )

    # Error troubleshooting
    fix = assistant.troubleshoot_error(
        error_message="TypeError: Cannot read property 'map' of undefined",
        technology="React",
        context="Fetching data in useEffect"
    )

    # Security check
    security = assistant.check_security(
        package="lodash",
        version="4.17.15",
        ecosystem="npm"
    )