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Prerequisites

  • pip install trajectory-sdk
  • A LangSmith API key (starts with lsv2_pt_...)
  • A LangSmith project ID with existing traces

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Walkthrough

import trajectory_sdk as tj

# 1. Initialize
tj.init(
    provider="langsmith",
    api_key="lsv2_pt_...",
    project_id="your-project-id",
    trajectory_api_key="your-trajectory-api-key",  # required for upload
)

# 2. List conversations
conversations = tj.list_conversations(limit=5)

# 3. Extract IDs and import as Trajectories
ids = [c.conversation_id for c in conversations]
trajectories = tj.import_conversations(ids)

# 4. Upload to the Trajectory platform
tj.upload(trajectories, dataset="my-dataset-v1")
You can also save to disk instead of (or in addition to) uploading: 
tj.save(trajectories, "./exports")
Each conversation becomes one JSON file in ./exports/, named by conversation ID.

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Import by ID

If you already know which conversations you want: 
trajectories = tj.import_conversations([
    "cc_abc123",
    "cc_def456",
])

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LangSmith Notes

  • Conversations are identified by conversation_id or session_id in run metadata. Runs without either are treated as standalone conversations.
  • Roles are normalized: human → user, ai → assistant.
  • API responses are cached in-memory for 5 minutes to reduce load on repeated imports.