feat: integrate backend

.gitignore

@@ -42,6 +42,10 @@ examples/**/*.json
 !examples/**/package.json
 !examples/**/package-lock.json
 
+
+# Exception
+!examples/semiconductor/semiconductor-ui/api/poetry.lock
+
 .openssa/
 test*.ipynb
 tmp/

examples/semiconductor/semiconductor-ui/api/Dockerfile

@@ -1,6 +1,7 @@
-FROM --platform=linux/amd64 python:3.10-slim AS base
+FROM --platform=linux/amd64 python:3.12-slim AS base
 
 # Install Poetry
+RUN apt update -y && apt upgrade -y && apt install git -y
 RUN apt update -y && apt install poppler-utils -y
 RUN python -m pip install --upgrade pip && \
     pip install --no-cache-dir poetry==1.3.2
@@ -11,15 +12,15 @@ RUN poetry config virtualenvs.in-project true && \
 
 WORKDIR /api
 
-COPY pyproject.toml /api/
+COPY pyproject.toml poetry.lock /api/
 
 # =======================================
 # Build image
 FROM base AS build
-
+ENV POETRY_REQUESTS_TIMEOUT=300
+ENV PIP_DEFAULT_TIMEOUT=300
 RUN poetry install
 
-
 # =======================================
 # App image
 FROM base AS app

examples/semiconductor/semiconductor-ui/api/data_and_knowledge.py

@@ -0,0 +1,35 @@
+from __future__ import annotations
+
+from pathlib import Path
+from typing import TYPE_CHECKING
+
+from dotenv import load_dotenv
+import yaml
+
+if TYPE_CHECKING:
+    from openssa.core.programming.hierarchical.plan import HTPDict
+
+
+load_dotenv()
+
+
+EXPERT_KNOWLEDGE_FILE_PATH: Path = Path(__file__).parent / 'expert-knowledge.txt'
+with open(file=EXPERT_KNOWLEDGE_FILE_PATH,
+          buffering=-1,
+          encoding='utf-8',
+          errors='strict',
+          newline=None,
+          closefd=True,
+          opener=None) as f:
+    EXPERT_KNOWLEDGE: str = f.read()
+
+
+EXPERT_PROGRAM_SPACE_FILE_PATH: Path = Path(__file__).parent / 'expert-program-space.yml'
+with open(file=EXPERT_PROGRAM_SPACE_FILE_PATH,
+          buffering=-1,
+          encoding='utf-8',
+          errors='strict',
+          newline=None,
+          closefd=True,
+          opener=None) as f:
+    EXPERT_PROGRAM_SPACE: dict[str, HTPDict] = yaml.safe_load(stream=f)

examples/semiconductor/semiconductor-ui/api/expert-knowledge.txt

@@ -0,0 +1,62 @@
+Etching Silicon Dioxide (SiO2): typical recipe(s)
+=================================================
+
+If using Inductively Coupled Plasma (ICP) Reactive Ion Etching (RIE)
+--------------------------------------------------------------------
+
+
+GASES & FLOW RATES:
+
+Common gas is CHF3, often mixed with small amount of Ar and/or O2:
+- CHF3 provides fluorine for etching while also polymerising to provide sidewall protection, improving anisotropy
+- Ar helps maintain stable plasma
+- O2 enhances volatility of etch products
+
+Typical starting point:
+- 20-50 sccm of CHF3
+- 5-10 sccm of Ar
+- 2-5 sccm of O2
+
+
+ICP POWER:
+
+Higher ICP power (e.g., 500-1000W) increases plasma density and etch rate
+BUT may also lead to more physical damage and less anisotropic profiles
+
+
+RF POWER:
+
+Lower RF power (e.g., 10-50W) provides more anisotropic profiles
+
+
+PRESSURE:
+
+Lower pressure (e.g., 5-20 mTorr) helps improve anisotropy
+
+
+ETCH TIME:
+
+You need to adjust etch time depending on desired depth and etch rate.
+
+Remember that etch rate can vary across wafer and over time, so it's best to overestimate time and measure depth periodically.
+
+
+END-POINT DETECTION:
+
+Many RIE systems have optical emission spectroscopy (OES) or interferometry for end-point detection.
+These can stop etching process when desired depth is reached.
+
+
+OPTIMIZATION CONSIDERATIONS:
+
+- Etch rate
+- Selectivity to mask and underlying layers
+- Etch profile (anisotropy)
+- Uniformity
+- Physical or chemical damage
+
+
+SAFETY PROCEDURES:
+
+- Always follow safety procedures when working with plasma etching systems and handling gases
+- Confirm with facility and equipment manager that your planned recipe is compatible and won't cause any damage or contamination

examples/semiconductor/semiconductor-ui/api/expert-program-space.yml

@@ -0,0 +1,17 @@
+plan:
+  task: |-
+    For etching PECVD SiO2 using Inductively Coupled Plasma (ICP) Reactive Ion Etching (RIE),
+    recommend 2 good parameter sets and their relative advantages/disadvantages
+  
+  sub-htps:
+    - task: |-
+        Get typical gases used for such process and their flow rate ranges
+        in SiO2 etching using Inductively Coupled Plasma (ICP) Reactive Ion Etching (RIE)
+        
+    - task: |-    
+        Get typical ICP Power, RF Power and Pressure value ranges and associated trade-offs
+        in SiO2 etching using Inductively Coupled Plasma (ICP) Reactive Ion Etching (RIE)
+
+    - task: |-
+        Recommend 2 parameter sets (each including Flow Rate for each Gas, plus ICP Power, RF Power and Pressure)
+        with analysis of their relative pros and cons.

examples/semiconductor/semiconductor-ui/api/main.py

@@ -3,6 +3,36 @@
 from fastapi.middleware.cors import CORSMiddleware
 from collections import defaultdict
 import openai
+from openssa import Agent, ProgramSpace, HTP, HTPlanner, OpenAILM
+
+
+# pylint: disable=wrong-import-order
+from data_and_knowledge import EXPERT_PROGRAM_SPACE, EXPERT_KNOWLEDGE
+from semikong_lm import SemiKongLM
+
+
+def get_or_create_agent(
+    use_semikong_lm: bool = True, max_depth=2, max_subtasks_per_decomp=4
+) -> Agent:
+    lm = (SemiKongLM if use_semikong_lm else OpenAILM).from_defaults()
+
+    program_space = ProgramSpace(lm=lm)
+    if EXPERT_PROGRAM_SPACE:
+        for program_name, htp_dict in EXPERT_PROGRAM_SPACE.items():
+            htp = HTP.from_dict(htp_dict)
+            program_space.add_or_update_program(
+                name=program_name, description=htp.task.ask, program=htp
+            )
+
+    return Agent(
+        program_space=program_space,
+        programmer=HTPlanner(
+            lm=lm, max_depth=max_depth, max_subtasks_per_decomp=max_subtasks_per_decomp
+        ),
+        knowledge={EXPERT_KNOWLEDGE} if EXPERT_KNOWLEDGE else None,
+        resources={},
+    )
+
 
 app = FastAPI()
 
@@ -14,18 +44,23 @@
     allow_headers=["*"],
 )
 
-client = openai.OpenAI(api_key=os.environ['OPENAI_API_KEY'])
+client = openai.OpenAI(api_key=os.environ["OPENAI_API_KEY"])
+
 
 def call_gpt(prompt):
     response = client.chat.completions.create(
         model="gpt-4o",
         messages=[
-            {"role": "system", "content": "You are an expert in parsing text into a specific format. Please help me with this task."},
-            {"role": "user", "content": prompt}
-        ]
+            {
+                "role": "system",
+                "content": "You are an expert in parsing text into a specific format. Please help me with this task.",
+            },
+            {"role": "user", "content": prompt},
+        ],
     )
     return response.choices[0].message.content
 
+
 def parse_recipe_text(text):
     parsed_data = {"recipe_1": "", "recipe_2": "", "agent_advice": ""}
     lines = text.split("\n")
@@ -44,14 +79,17 @@ def parse_recipe_text(text):
     parsed_data = {key: value.strip() for key, value in parsed_data.items()}
     return parsed_data
 
+
 def solve_semiconductor_question(question):
     solutions = defaultdict(str)
 
-    solutions[question] = get_or_create_agent(use_semikong_lm=True).solve(problem=question)
+    solutions[question] = get_or_create_agent(use_semikong_lm=True).solve(
+        problem=question
+    )
 
     solution = solutions[question]
-    solution = solution.replace('$', r'\$')
-    
+    solution = solution.replace("$", r"\$")
+
     prompt = f"""{solution} \n\n Please help me parse the above text into this format:\n
          recipe_1: Show the recipe 1 here\n 
          recipe_2: Show the recipe 2 here\n
@@ -62,25 +100,26 @@ def solve_semiconductor_question(question):
     parsed_solution = parse_recipe_text(solution)
     return parsed_solution
 
+
 @app.get("/")
 async def root():
     return {"message": "Hello World"}
 
+
 @app.get("/data")
 async def get_data():
     return {"data": "data"}
 
+
 @app.post("/data")
-async def post_data(request: Request):
-    data = await request.json()
-    question = data.get('question')
+async def post_data(data: dict):
+    question = data.get("question")
     if not question:
         return {"error": "No question provided"}, 400
 
     try:
         parsed_answer = solve_semiconductor_question(question)
         return parsed_answer
     except Exception as e:
-        logger.error(f"Error solving the question: {e}")
+        print(f"Error solving the question: {e}")
         return {"error": str(e)}, 500
-