Course materials for LangSmith Professional, with Python and TypeScript implementations.
Both python/ and ts/ directories mirror each other with equivalent implementations.
βββ python/
β βββ officeflow-agent/ # OfficeFlow customer support agent (Emma)
β β βββ agent_v0.py # Baseline agent (no tracing)
β β βββ agent_v1.py # + LangSmith tracing
β β βββ agent_v2.py # + Enhanced tool instructions
β β βββ agent_v3.py # + Stock information policy
β β βββ agent_v4.py # + No-chunking RAG
β β βββ agent_v5.py # + Conciseness improvements
β β βββ inventory/ # SQLite product database
β β βββ knowledge_base/ # Company policy documents + embeddings
β β
β βββ module-1/
β β βββ lesson-2/ # Tracing with LangSmith
β β βββ third_party_agent.py # Weather agent with tool calling
β β βββ thread_agent.py # Conversational agent with threads
β β
β βββ module-2/ # Evaluation fundamentals
β β βββ lesson-3/ # Running experiments
β β β βββ run_experiment.py
β β βββ lesson-4/ # Code-based evaluation
β β β βββ eval_schema_check.py # Schema-before-query evaluator
β β β βββ run_eval.py
β β βββ lesson-5/ # LLM-as-judge
β β β βββ run_experiment.py
β β βββ lesson-6/ # Pairwise evaluation
β β βββ run_agents.py
β β βββ eval_conciseness_pairwise.py
β β βββ run_pairwise_experiment.py
β β
β βββ module-3/ # Production & scaling
β β βββ lesson-2/ # Trace upload
β β βββ generate_traces.py
β β βββ upload_traces.py
β β
β βββ pyproject.toml
β βββ .env.example
β
βββ ts/
βββ officeflow-agent/ # OfficeFlow customer support agent (Emma)
β βββ agent_v0.ts # Baseline agent (no tracing)
β βββ agent_v1.ts # + LangSmith tracing
β βββ agent_v2.ts # + Enhanced tool instructions
β βββ agent_v3.ts # + Stock information policy
β βββ agent_v4.ts # + No-chunking RAG
β βββ agent_v5.ts # + Conciseness improvements
β βββ inventory/ # SQLite product database
β βββ knowledge_base/ # Company policy documents + embeddings
β
βββ module-1/
β βββ lesson-2/ # Tracing with LangSmith
β βββ third_party_agent.ts # Weather agent with tool calling
β βββ thread_agent.ts # Conversational agent with threads
β
βββ module-2/ # Evaluation fundamentals
β βββ lesson-3/ # Running experiments
β β βββ run_experiment.ts
β βββ lesson-4/ # Code-based evaluation
β β βββ eval_schema_check.ts # Schema-before-query evaluator
β β βββ run_eval.ts
β βββ lesson-5/ # LLM-as-judge
β β βββ run_experiment.ts
β βββ lesson-6/ # Pairwise evaluation
β βββ run_agents.ts
β βββ eval_conciseness_pairwise.ts
β βββ run_pairwise_experiment.ts
β
βββ module-3/ # Production & scaling
β βββ lesson-2/ # Trace upload
β βββ generate_traces.ts
β βββ upload_traces.ts
β
βββ package.json
βββ example.env