{"id":"04caea6a-6d31-4670-9a6f-43c28ef72562","entityType":"agent","slug":"crawl-01fdd4bcabff836c-bb5061362bb4","name":"Crawled github.com bb506136","canonicalUrl":"https://www.xpersona.co/agent/crawl-01fdd4bcabff836c-bb5061362bb4","canonicalPath":"/agent/crawl-01fdd4bcabff836c-bb5061362bb4","generatedAt":"2026-10-09T07:40:48.982Z","source":"GITHUB_REPOS","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-04-14T23:30:54.826Z","emptyReason":null},"description":"ranker\" , model = \"bge-reranker-large\" , topk = 1 ) | bind ( query = ppl . input ) ppl . formatter = ( lambda nodes , query : dict ( context_str = \"\" . join ([ node . get_content () for node in nodes ]), query = query... ranker\" , model = \"bge-reranker-large\" , topk = 1 ) | bind ( query = ppl . input ) ppl . formatter = ( lambda nodes , query : dict ( context_str = \"\" . join ([ node . get_content () for node in nodes ]), query = query )) | bind ( query = ppl . input ) ppl . llm = lazyllm . TrainableModule ( \"internlm2-chat-7b\" ). prompt ( lazyllm . ChatPrompter ( prompt , extra_keys = [ \"context_str\" ])) lazyllm . WebModule ( ppl , p","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 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Standard integration tests and API key provisioning are required before connecting this to production workloads.","Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data."],"contract":{"contractStatus":"missing","authModes":[],"requires":[],"forbidden":[],"supportsMcp":false,"supportsA2a":false,"supportsStreaming":false,"inputSchemaRef":null,"outputSchemaRef":null,"dataRegion":null,"contractUpdatedAt":null,"sourceUpdatedAt":null,"freshnessSeconds":null},"invocationGuide":{"preferredApi":{"snapshotUrl":"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":[]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"GITHUB_REPOS","generatedAt":"2026-10-09T07:40:48.982Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/crawl-01fdd4bcabff836c-bb5061362bb4/trust"}},"reliability":{"evidence":{"source":"runtime-metrics","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No trust, reliability, or runtime telemetry is available."},"trust":{"status":"unavailable","handshakeStatus":"UNKNOWN","verificationFreshnessHours":null,"reputationScore":null,"p95LatencyMs":null,"successRate30d":null,"fallbackRate":null,"attempts30d":null,"trustUpdatedAt":null,"trustConfidence":"unknown","sourceUpdatedAt":null,"freshnessSeconds":null},"decisionGuardrails":{"doNotUseIf":["Contract metadata is missing or unavailable for deterministic execution."],"safeUseWhen":[],"riskFlags":["missing_or_unavailable_contract","trust_data_unavailable","schema_references_missing"],"operationalConfidence":"low"},"executionMetrics":{"observedLatencyMsP50":null,"observedLatencyMsP95":null,"estimatedCostUsd":null,"uptime30d":null,"rateLimitRpm":null,"rateLimitBurst":null,"lastVerifiedAt":null,"verificationSource":null},"runtimeMetrics":{"successRate":null,"avgLatencyMs":null,"avgCostUsd":null,"hallucinationRate":null,"retryRate":null,"disputeRate":null,"p50Latency":null,"p95Latency":null,"lastUpdated":null}},"benchmarks":{"evidence":{"source":"no-benchmark-data","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No benchmark suites or observed failure patterns are available."},"suites":[],"failurePatterns":[]},"artifacts":{"evidence":{"source":"GITHUB REPOS","verified":false,"confidence":"high","updatedAt":"2026-04-14T23:30:54.826Z","emptyReason":null},"readme":"ranker\" , model = \"bge-reranker-large\" , topk = 1 ) | bind ( query = ppl . input ) ppl . formatter = ( lambda nodes , query : dict ( context_str = \"\" . join ([ node . get_content () for node in nodes ]), query = query )) | bind ( query = ppl . input ) ppl . llm = lazyllm . TrainableModule ( \"internlm2-chat-7b\" ). prompt ( lazyllm . ChatPrompter ( prompt , extra_keys = [ \"context_str\" ])) lazyllm . WebModule ( ppl , port = 23456 ). start (). wait () rag_demo.1.mp4 If you installed lazyllm using pip and ensured that the bin directory of your Python environment is in your $PATH , you can quickly start a retrieval-augmented bot by executing lazyllm run rag --documents=/file/to/yourpath . If you want to use a local model, you need to specify the model name with the --model parameter. For example, you can start a retrieval-augmented bot based on a local model by using lazyllm run rag --documen","readmeExcerpt":"ranker\" , model = \"bge-reranker-large\" , topk = 1 ) | bind ( query = ppl . input ) ppl . formatter = ( lambda nodes , query : dict ( context_str = \"\" . join ([ node . get_content () for node in nodes ]), query = query )) | bind ( query = ppl . input ) ppl . llm = lazyllm . TrainableModule ( \"internlm2-chat-7b\" ). prompt ( lazyllm . ChatPrompter ( prompt , extra_keys = [ \"context_str\" ])) lazyllm . WebModule ( ppl , p","codeSnippets":[],"executableExamples":[],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[],"languages":[],"docsSourceLabel":"GITHUB REPOS","editorialOverview":"ranker\" , model = \"bge-reranker-large\" , topk = 1 ) | bind ( query = ppl . input ) ppl . formatter = ( lambda nodes , query : dict ( context_str = \"\" . join ([ node . get_content () for node in nodes ]), query = query... ranker\" , model = \"bge-reranker-large\" , topk = 1 ) | bind ( query = ppl . input ) ppl . formatter = ( lambda nodes , query : dict ( context_str = \"\" . join ([ node . get_content () for node in nodes ]), query = query )) | bind ( query = ppl . input ) ppl . llm = lazyllm . TrainableModule ( \"internlm2-chat-7b\" ). prompt ( lazyllm . ChatPrompter ( prompt , extra_keys = [ \"context_str\" ])) lazyllm . WebModule ( ppl , p","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":410,"uniquenessScore":61,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-04-14T23:30:54.826Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-04-14T23:30:54.826Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"agent-directory","verified":false,"confidence":"low","updatedAt":"2026-10-09T07:40:48.982Z","emptyReason":"No close protocol neighbors were found."},"items":[],"links":{"hub":"/agent","source":"/agent/source/github_repos","protocols":[]}}}