73 lines
3.2 KiB
Markdown
73 lines
3.2 KiB
Markdown
# Backend
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The backend owns the application API and CAD generation workflow:
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- `app/`: HTTP API, jobs, orchestration, and persistence adapters.
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- `agent/`: AI prompts, tools, and skills used by the generation agent.
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- `engine/`: CDSL compiler, sketch solver, and STEP generation runtime.
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- `cdsl_library/`: Official CDSL examples, metadata, and search index.
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- `tests/`: Engine, API, and end-to-end generation tests.
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Expected development entrypoint: `app.main:app`, served by Uvicorn.
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## Reasoning Effort
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The backend uses the Chat Completions API. Configure a provider's reasoning
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budget with `CDSL_<PROVIDER>_REASONING_EFFORT`; for the current OpenAI setup:
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```dotenv
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CDSL_OPENAI_REASONING_EFFORT=medium
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```
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Use `low`, `medium`, or `high` according to the latency/cost versus quality
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tradeoff. The setting is sent as Chat Completions' `reasoning_effort` field to
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authoring, streaming, and visual-review requests. Leave it empty to use the
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provider/model default. The selected OpenAI-compatible endpoint must support
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the requested value.
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## Autonomous CDSL Agent Configuration
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The autonomous agent writes one frozen free-form `requirements.md`, then
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observes, measures, renders and appends one CDSL feature at a time. Its author
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uses normal function calls; no provider strict JSON Schema capability or
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complete modelling DAG is required. Candidate fragments are rebuilt in a
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staging directory through `cdsl_only` before a checkpoint can be committed.
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Final publication requires a separately configured vision-capable review model
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and the Python OpenCascade/Pillow technical renderer. The agent may build and
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inspect intermediate checkpoints without image review; a final run fails
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closed if its independent review configuration is unavailable.
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```dotenv
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# Must name one configured provider and one model listed in that provider's
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# CDSL_<PROVIDER>_VISION_MODELS setting. It is intentionally not inferred
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# from the authoring model.
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CDSL_REVIEW_PROVIDER=deepseek
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CDSL_REVIEW_MODEL=deepseek-v4-flash-vision-exp
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CDSL_DEEPSEEK_VISION_MODELS=deepseek-v4-flash-vision-exp
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# Install Python rendering dependencies. The renderer reads the revision STEP
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# file and creates canonical images without a browser or GPU driver.
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pip install -r requirements.txt
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# Limits apply to the current checkpoint head, never to total task complexity.
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CDSL_AGENT_TOOL_CALLS_PER_CYCLE=12
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CDSL_AGENT_CANDIDATE_ATTEMPTS_PER_HEAD=3
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CDSL_AGENT_CONSECUTIVE_NO_PROGRESS_LIMIT=6
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CDSL_AGENT_MAX_FEATURES_PER_FRAGMENT=6
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CDSL_AGENT_CONTEXT_CHAR_LIMIT=24000
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CDSL_AGENT_RENDER_CACHE=true
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```
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The author chooses each coherent 1-6 feature batch. Every rebuilt batch is
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rendered and independently reviewed before it can become a checkpoint; only
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an accepted reviewer verdict advances the working model. Every checkpoint is rebuilt from its fully materialized CDSL through the
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`cdsl_only` runtime. Checkpoint GLB files are preview-only; STEP, CDSL, and
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reports are available only after the task reaches `COMPLETED`.
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The backend assigns feature and sketch IDs, appends causal dependencies and
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expands only opaque current-snapshot selector tokens. It does not compile
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geometry templates or correct workplanes, profiles, sizes, directions or
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boolean semantics authored by the model. Failed candidates remain auditable
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but never become revisions.
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