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77 lines
3.1 KiB
C#
77 lines
3.1 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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using Azure.AI.Projects;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.AI;
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using Neo4j.AgentFramework.GraphRAG;
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using Neo4j.Driver;
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var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
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var neo4jUri = Environment.GetEnvironmentVariable("NEO4J_URI") ?? throw new InvalidOperationException("NEO4J_URI is not set.");
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var neo4jUsername = Environment.GetEnvironmentVariable("NEO4J_USERNAME") ?? "neo4j";
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var neo4jPassword = Environment.GetEnvironmentVariable("NEO4J_PASSWORD") ?? throw new InvalidOperationException("NEO4J_PASSWORD is not set.");
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var fulltextIndex = Environment.GetEnvironmentVariable("NEO4J_FULLTEXT_INDEX_NAME") ?? "search_chunks";
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const string RetrievalQuery = """
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MATCH (node)-[:FROM_DOCUMENT]->(doc:Document)<-[:FILED]-(company:Company)
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OPTIONAL MATCH (company)-[:FACES_RISK]->(risk:RiskFactor)
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WITH node, score, company, doc, collect(DISTINCT risk.name)[0..5] AS risks
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OPTIONAL MATCH (company)-[:MENTIONS]->(product:Product)
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WITH node, score, company, doc, risks, collect(DISTINCT product.name)[0..5] AS products
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RETURN
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node.text AS text,
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score,
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company.name AS company,
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company.ticker AS ticker,
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doc.title AS title,
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risks,
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products
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ORDER BY score DESC
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""";
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await using var driver = GraphDatabase.Driver(new Uri(neo4jUri), AuthTokens.Basic(neo4jUsername, neo4jPassword));
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await driver.VerifyConnectivityAsync();
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await using var provider = new Neo4jContextProvider(
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driver,
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new Neo4jContextProviderOptions
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{
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IndexName = fulltextIndex,
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IndexType = IndexType.Fulltext,
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RetrievalQuery = RetrievalQuery,
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TopK = 5,
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ContextPrompt = "Use the retrieved Neo4j graph context to answer accurately and call out when context is missing."
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});
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
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// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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AIAgent agent = new AIProjectClient(
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new Uri(endpoint),
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new DefaultAzureCredential())
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.AsAIAgent(new ChatClientAgentOptions
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{
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ChatOptions = new()
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{
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ModelId = deploymentName,
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Instructions = "You are a helpful assistant that answers questions using Neo4j graph context."
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},
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AIContextProviders = [provider]
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});
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AgentSession session = await agent.CreateSessionAsync();
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foreach (var question in new[]
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{
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"What products does Microsoft offer?",
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"What risks does Apple face?",
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"Tell me about NVIDIA's AI business and risk factors."
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})
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{
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Console.WriteLine($">> {question}\n");
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Console.WriteLine(await agent.RunAsync(question, session));
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Console.WriteLine();
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}
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