env file changes

Dockerfile

@@ -1,13 +1,17 @@
-FROM python:3.9
+    FROM python:3.9
 
-RUN useradd -m -u 1000 user
-USER user
-ENV PATH="/home/user/.local/bin:$PATH"
+    RUN useradd -m -u 1000 user
+    USER user
+    ENV PATH="/home/user/.local/bin:$PATH"
+    ENV GROQ_API_KEY=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
+    ENV NEO4J_USERNAME=neo4j
+    ENV NEO4J_PASSWORD=tYteIJBUYXbdgwSxKqZXWZ87b2XChS7wfB2Ijt7LLDs
+    ENV NEO4J_URI=neo4j+s://2e177e83.databases.neo4j.io
 
-WORKDIR /app
+    WORKDIR /app
 
-COPY --chown=user ./requirements.txt requirements.txt
-RUN pip install --no-cache-dir --upgrade -r requirements.txt
+    COPY --chown=user ./requirements.txt requirements.txt
+    RUN pip install --no-cache-dir --upgrade -r requirements.txt
 
-COPY --chown=user . /app
-CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]
+    COPY --chown=user . /app
+    CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

routers/Query/query.py

@@ -13,7 +13,7 @@ global rag
 def instantiate_dependencies():
 
     embedding_model = HuggingFaceEmbeddings(model_name = 'NeuML/pubmedbert-base-embeddings')
-    llm = ChatGroq(groq_api_key=os.getenv('groq_api'), model_name='gemma2-9b-it')
+    llm = ChatGroq(groq_api_key=os.getenv('GROQ_API_KEY'), model_name='gemma2-9b-it')
     
     graph = Neo4jGraph(
         url = os.getenv('NEO4J_URI'),