Résultats de recherche

from anthropic.types import (
    MessageParam,
    TextBlockParam,
    SearchResultBlockParam,
    ToolResultBlockParam,
)

client = Anthropic()

# Définir un outil de recherche dans la base de connaissances
knowledge_base_tool = {
    "name": "search_knowledge_base",
    "description": "Search the company knowledge base for information",
    "input_schema": {
        "type": "object",
        "properties": {"query": {"type": "string", "description": "The search query"}},
        "required": ["query"],
    },
}


# Fonction de traitement de l'appel d'outil
def search_knowledge_base(query):
    # Votre logique de recherche ici
    # Renvoie les résultats de recherche au format attendu
    return [
        SearchResultBlockParam(
            type="search_result",
            source="https://docs.company.com/product-guide",
            title="Product Configuration Guide",
            content=[
                TextBlockParam(
                    type="text",
                    text="To configure the product, navigate to Settings > Configuration. The default timeout is 30 seconds, but can be adjusted between 10-120 seconds based on your needs.",
                )
            ],
            citations={"enabled": True},
        ),
        SearchResultBlockParam(
            type="search_result",
            source="https://docs.company.com/troubleshooting",
            title="Troubleshooting Guide",
            content=[
                TextBlockParam(
                    type="text",
                    text="If you encounter timeout errors, first check the configuration settings. Common causes include network latency and incorrect timeout values.",
                )
            ],
            citations={"enabled": True},
        ),
    ]


# Construire la conversation dans une liste, en commençant par la question de l'utilisateur
messages: list[MessageParam] = [
    {"role": "user", "content": "How do I configure the timeout settings?"}
]

# Créer un message avec l'outil
response = client.messages.create(
    model="claude-opus-5",
    max_tokens=1024,
    tools=[knowledge_base_tool],
    tool_choice={
        "type": "tool",
        "name": "search_knowledge_base",
        "disable_parallel_tool_use": True,
    },
    messages=messages,
)

# Lorsque Claude appelle l'outil, fournir les résultats de recherche.
# Le bloc tool_use n'est pas toujours en premier : itérer pour le trouver.
tool_use = next((block for block in response.content if block.type == "tool_use"), None)
if tool_use is not None:
    tool_result = search_knowledge_base(tool_use.input["query"])

    # Ajouter le tour de Claude, puis le résultat de l'outil, à la conversation en cours
    messages.append({"role": "assistant", "content": response.content})
    messages.append(
        {
            "role": "user",
            "content": [
                ToolResultBlockParam(
                    type="tool_result",
                    tool_use_id=tool_use.id,
                    content=tool_result,  # Search results go here
                )
            ],
        }
    )

    # Renvoyer le résultat de l'outil
    final_response = client.messages.create(
        model="claude-opus-5",
        max_tokens=1024,
        messages=messages,
    )
    print(final_response)

from anthropic.types import TextBlockParam, SearchResultBlockParam

client = Anthropic()

# Fournissez les résultats de recherche directement dans le message utilisateur.
response = client.messages.create(
    model="claude-opus-5-5",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": [
                SearchResultBlockParam(
                    type="search_result",
                    source="https://docs.company.com/api-reference",
                    title="API Reference - Authentication",
                    content=[
                        TextBlockParam(
                            type="text",
                            text="All API requests must include an API key in the Authorization header. Keys can be generated from the dashboard. Rate limits: 1000 requests per hour for standard tier, 10000 for premium.",
                        )
                    ],
                    citations={"enabled": True},
                ),
                SearchResultBlockParam(
                    type="search_result",
                    source="https://docs.company.com/quickstart",
                    title="Getting Started Guide",
                    content=[
                        TextBlockParam(
                            type="text",
                            text="To get started: 1) Sign up for an account, 2) Generate an API key from the dashboard, 3) Install our SDK using pip install company-sdk, 4) Initialize the client with your API key.",
                        )
                    ],
                    citations={"enabled": True},
                ),
                TextBlockParam(
                    type="text",
                    text="Based on these search results, how do I authenticate API requests and what are the rate limits?",
                ),
            ],
        }
    ],
)

print(response)

from anthropic.types import (
    SearchResultBlockParam,
    TextBlockParam,
    ToolResultBlockParam,
    ToolUseBlockParam,
)

client = Anthropic()

knowledge_base_tool = {
    "name": "search_knowledge_base",
    "description": "Search the company knowledge base for information",
    "input_schema": {
        "type": "object",
        "properties": {"query": {"type": "string", "description": "The search query"}},
        "required": ["query"],
    },
}

# Rejoue une conversation qui fournit des résultats de recherche des deux façons : le premier
# message utilisateur contient un résultat pré-récupéré, et le résultat d'outil en renvoie un autre
response = client.messages.create(
    model="claude-opus-5-5",
    max_tokens=1024,
    tools=[knowledge_base_tool],
    messages=[
        {
            "role": "user",
            "content": [
                SearchResultBlockParam(
                    type="search_result",
                    source="https://docs.company.com/overview",
                    title="Product Overview",
                    content=[
                        TextBlockParam(
                            type="text",
                            text="Acme Dashboard is a monitoring tool for distributed systems. It supports real-time alerting and custom metric dashboards.",
                        )
                    ],
                    citations={"enabled": True},
                ),
                TextBlockParam(
                    type="text",
                    text="What does Acme Dashboard do, and what plans is it available on?",
                ),
            ],
        },
        {
            "role": "assistant",
            "content": [
                TextBlockParam(
                    type="text", text="Let me check the pricing information."
                ),
                ToolUseBlockParam(
                    type="tool_use",
                    id="toolu_01A09q90qw90lq917835lq9",
                    name="search_knowledge_base",
                    input={"query": "Acme Dashboard pricing plans"},
                ),
            ],
        },
        {
            "role": "user",
            "content": [
                ToolResultBlockParam(
                    type="tool_result",
                    tool_use_id="toolu_01A09q90qw90lq917835lq9",
                    content=[
                        SearchResultBlockParam(
                            type="search_result",
                            source="https://docs.company.com/pricing",
                            title="Pricing Plans",
                            content=[
                                TextBlockParam(
                                    type="text",
                                    text="Acme Dashboard is available on the Starter plan at $10 per user per month and the Enterprise plan with custom pricing.",
                                )
                            ],
                            citations={"enabled": True},
                        )
                    ],
                )
            ],
        },
    ],
)

print(response)