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Agente de web search construido e implementado(Tavily ejemplo de .env en readme)

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Sebastian
2025-11-08 10:18:32 +00:00
parent 70f2a42502
commit a23f45ca6d
9 changed files with 358 additions and 6 deletions
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3
README.md
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@@ -0,0 +1,3 @@
Asi debe estar en el .env para el agente de web search
TAVILY_API_KEY=

37
backend/app/agents/web_search/__init__.py Normal file
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@@ -0,0 +1,37 @@
from __future__ import annotations
from .agent import agent
from .models import WebSearchResponse, WebSearchState
async def search_web(
query: str,
max_results: int = 5,
include_raw_content: bool = False,
) -> WebSearchResponse:
"""
Execute web search using Tavily MCP server.
Args:
query: Search query string
max_results: Maximum number of results to return (1-10)
include_raw_content: Whether to include full content in results
Returns:
WebSearchResponse with results and summary
"""
state = WebSearchState(
user_query=query,
max_results=max_results,
include_raw_content=include_raw_content,
)
prompt = (
f"Search the web for: {query}\n\n"
f"Return the top {max_results} most relevant results. "
"Provide a concise summary of the key findings."
)
# Ejecutar agente con Tavily API directa
result = await agent.run(prompt, deps=state)
return result.output

72
backend/app/agents/web_search/agent.py Normal file
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@@ -0,0 +1,72 @@
from __future__ import annotations
from pydantic_ai import Agent, RunContext
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.azure import AzureProvider
from tavily import TavilyClient
from app.core.config import settings
from .models import WebSearchResponse, WebSearchState, SearchResult
provider = AzureProvider(
azure_endpoint=settings.AZURE_OPENAI_ENDPOINT,
api_version=settings.AZURE_OPENAI_API_VERSION,
api_key=settings.AZURE_OPENAI_API_KEY,
)
model = OpenAIChatModel(model_name="gpt-4o", provider=provider)
tavily_client = TavilyClient(api_key=settings.TAVILY_API_KEY)
agent = Agent(
model=model,
name="WebSearchAgent",
deps_type=WebSearchState,
output_type=WebSearchResponse,
system_prompt=(
"You are a web search assistant powered by Tavily. "
"Use the tavily_search tool to find relevant, up-to-date information. "
"Return a structured WebSearchResponse with results and a concise summary. "
"Always cite your sources with URLs."
),
)
@agent.tool
def tavily_search(ctx: RunContext[WebSearchState], query: str) -> list[SearchResult]:
"""Search the web using Tavily API for up-to-date information."""
response = tavily_client.search(
query=query,
max_results=ctx.deps.max_results,
search_depth="basic",
include_raw_content=ctx.deps.include_raw_content,
)
results = []
for item in response.get("results", []):
results.append(
SearchResult(
title=item.get("title", ""),
url=item.get("url", ""),
content=item.get("content", ""),
score=item.get("score"),
)
)
return results
@agent.output_validator
def finalize_response(
ctx: RunContext[WebSearchState],
response: WebSearchResponse,
) -> WebSearchResponse:
"""Post-process and validate the search response"""
return response.model_copy(
update={
"query": ctx.deps.user_query,
"total_results": len(response.results),
}
)

29
backend/app/agents/web_search/models.py Normal file
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@@ -0,0 +1,29 @@
from __future__ import annotations
from pydantic import BaseModel, Field
class SearchResult(BaseModel):
"""Individual search result from web search"""
title: str
url: str
content: str
score: float | None = None
class WebSearchState(BaseModel):
"""State passed to agent tools via deps"""
user_query: str
max_results: int = Field(default=5, ge=1, le=10)
include_raw_content: bool = False
class WebSearchResponse(BaseModel):
"""Structured response from the web search agent"""
query: str
results: list[SearchResult]
summary: str
total_results: int

5
backend/app/core/config.py
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@@ -37,7 +37,7 @@ class Settings(BaseSettings):
# Azure OpenAI configuración
AZURE_OPENAI_ENDPOINT: str
AZURE_OPENAI_API_KEY: str
AZURE_OPENAI_API_VERSION: str = "2024-02-01"
AZURE_OPENAI_API_VERSION: str = "2024-08-01-preview"
AZURE_OPENAI_EMBEDDING_MODEL: str = "text-embedding-3-large"
AZURE_OPENAI_EMBEDDING_DEPLOYMENT: str = "text-embedding-3-large"
@@ -57,6 +57,9 @@ class Settings(BaseSettings):
# LandingAI configuración
LANDINGAI_API_KEY: str
LANDINGAI_ENVIRONMENT: str = "production" # "production" o "eu"
TAVILY_API_KEY: str
# Schemas storage
SCHEMAS_DIR: str = "./data/schemas"

10
backend/app/routers/agent.py
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@@ -6,7 +6,7 @@ from pydantic_ai.ui.vercel_ai import VercelAIAdapter
from starlette.requests import Request
from starlette.responses import Response
from app.agents import form_auditor
from app.agents import form_auditor, web_search
from app.core.config import settings
provider = AzureProvider(
@@ -361,6 +361,14 @@ async def build_audit_report():
return result.model_dump()
@agent.tool_plain
async def search_web_information(query: str, max_results: int = 5):
"""Search the web for up-to-date information using Tavily. Use this when you need current information, news, research, or facts not in your knowledge base."""
result = await web_search.search_web(query=query, max_results=max_results)
return result.model_dump()
@router.post("/chat")
async def chat(request: Request) -> Response:
return await VercelAIAdapter.dispatch_request(request, agent=agent)

3
backend/pyproject.toml
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@@ -28,7 +28,8 @@ dependencies = [
# LandingAI Document AI
"landingai-ade>=0.2.1",
"redis-om>=0.3.5",
"pydantic-ai-slim[google,openai]>=1.11.1",
"pydantic-ai-slim[google,openai,mcp]>=1.11.1",
"tavily-python>=0.5.0",
]
[project.scripts]
dev = "uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload"

205
backend/uv.lock generated
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@@ -1,5 +1,5 @@
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@@ -74,13 +83,14 @@ dependencies = [
{ name = "openai" },
{ name = "pdf2image" },
{ name = "pillow" },
{ name = "pydantic-ai-slim", extra = ["google", "openai"] },
{ name = "pydantic-ai-slim", extra = ["google", "mcp", "openai"] },
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{ name = "python-dotenv" },
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{ name = "qdrant-client" },
{ name = "redis-om" },
{ name = "tavily-python" },
{ name = "tiktoken" },
{ name = "uvicorn", extra = ["standard"] },
{ name = "websockets" },
@@ -103,13 +113,14 @@ requires-dist = [
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{ name = "pdf2image", specifier = ">=1.17.0" },
{ name = "pillow", specifier = ">=11.0.0" },
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