Merge pull request #25 from ishan9678/master

[Release] v1.0

Author: ishan9678

.env.example

@@ -1,8 +1,6 @@
-#groq api key
-GROQ_API_KEY=
 #judge0 hosted api endpoint
 COMPILER_API_ENDPOINT=
 #postgres database url
 DATABASE_URL=
 #cors origins
-CORS_ORIGINS=
+CORS_ORIGINS=

backend/src/llama_agent.py

@@ -1,9 +1,7 @@
 import streamlit as st
 import asyncio
 import logging
-from typing import List, Optional
-from pydantic import BaseModel, Field
-from models import TestCase
+from models import PipelineRequest
 from pipeline import CodeGenerationPipeline
 from dotenv import load_dotenv
 import os
@@ -14,9 +12,9 @@
 
 load_dotenv()
 
-api_key = os.getenv("GROQ_API_KEY")
-if not api_key:
-    raise ValueError("GROQ API KEY is not set")
+# api_key = os.getenv("GROQ_API_KEY")
+# if not api_key:
+#     raise ValueError("GROQ API KEY is not set")
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)
@@ -57,17 +55,6 @@
     "gemma2-9b-it"
 ]
 
-
-class PipelineRequest(BaseModel):
-    model: str
-    language: str
-    question: str
-    explanation: Optional[str] = None
-    user_input: Optional[str] = None
-    max_iterations: int = 3
-    generate_test_cases: bool = True
-    test_cases: Optional[List[TestCase]] = []
-
 @app.post("/run_pipeline")
 async def run_pipeline(data: PipelineRequest):
     try:
@@ -90,7 +77,7 @@ async def run_pipeline(data: PipelineRequest):
         )
 
         pipeline = CodeGenerationPipeline(
-            api_key=os.getenv("GROQ_API_KEY"),
+            api_key=data.api_key,
             base_url="https://api.groq.com/openai/v1",
             max_iterations=data.max_iterations
         )
@@ -135,179 +122,4 @@ async def run_pipeline(data: PipelineRequest):
         raise HTTPException(status_code=500, detail=str(e))
 
 if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=8000, reload=True)
-
-
-# st.title("CodeCraft")
-
-# selected_model = st.selectbox(
-#     'Select a model:',
-#     model_ids
-# )
-
-# # Main input fields
-# question = st.text_area(
-#     "Question",
-#     placeholder="Write a function that returns the sum of two numbers",
-#     help="Enter the coding question or task."
-# )
-
-# explanation = st.text_area(
-#     "Explanation",
-#     placeholder="Create a simple function that takes two numbers as input and returns their sum.",
-#     help="Provide additional context or explanation."
-# )
-
-# user_input = st.text_input(
-#     "User Input (for testing)",
-#     placeholder="2 3",
-#     help="Input to test the generated code."
-# )
-
-
-# # Language dropdown
-# language = st.selectbox("Language", list(LANGUAGE_MAPPING.keys()), help="Select the programming language for the code.")
-# language_code = LANGUAGE_MAPPING[language]
-
-# # Slider for max iterations
-# max_iterations = st.slider("Max Iterations", min_value=1, max_value=5, value=3, help="Maximum number of iterations for the pipeline.")
-
-# # Test cases input
-# st.header("Test Cases")
-
-# # Option to generate test cases automatically
-# generate_test_cases = st.checkbox("Generate Test Cases Automatically", value=True, help="Automatically generate test cases based on the problem statement.")
-
-# # Initialize session state to store test cases
-# if "test_cases" not in st.session_state:
-#     st.session_state.test_cases = [{"input": "", "expected_output": ""}]  # Start with one test case
-
-# # Function to add a new test case
-# def add_test_case():
-#     st.session_state.test_cases.append({"input": "", "expected_output": ""})
-
-# # Collapsible section for test cases
-# with st.expander("Manage Test Cases", expanded=True):
-#     if not generate_test_cases:
-#         # Display test cases
-#         test_cases = []
-#         for i, test_case in enumerate(st.session_state.test_cases):
-#             st.subheader(f"Test Case {i + 1}")
-#             input_data = st.text_input(f"Input {i + 1}", value=test_case["input"], key=f"input_{i}", help="Input for the test case.")
-#             expected_output = st.text_input(f"Expected Output {i + 1}", value=test_case["expected_output"], key=f"expected_output_{i}", help="Expected output for the test case.")
-#             test_cases.append(TestCase(input=input_data, expected_output=expected_output))
-
-#         # Button to add more test cases
-#         st.button("Add Test Case", on_click=add_test_case)
-#     else:
-#         test_cases = []
-
-# # Run pipeline button
-# if st.button("Run Pipeline"):
-#     pipeline = CodeGenerationPipeline(
-#         api_key=api_key,
-#         base_url="https://api.groq.com/openai/v1",
-#         max_iterations=max_iterations
-#     )
-
-#     # Run the pipeline asynchronously
-#     async def run_pipeline_async():
-#         return await pipeline.run_pipeline(
-#             model = selected_model,
-#             language=language_code,
-#             question=question,
-#             test_cases=test_cases,
-#             explanation=explanation,
-#             user_input=user_input
-#         )
-
-#     # Display a spinner while the pipeline is running
-#     with st.spinner("Running pipeline..."):
-#         # Save the question to the database
-#         question = save_question(
-#             model=selected_model,
-#             question_text=question,
-#             explanation=explanation,
-#             user_input=user_input,
-#             language=language_code,
-#             max_iterations=max_iterations
-#         )
-#         result = asyncio.run(run_pipeline_async())
-
-#     # Display results
-#     st.header("Results")
-#     st.subheader("Chain of Thought")
-#     for i, step in enumerate(result.cot, 1):
-#         st.write(f"{i}. {step}")
-#     st.subheader("Final Code")
-#     st.code(result.final_code, language=language_code)
-
-#     st.subheader("Execution Result")
-#     st.text(result.final_result.output)
-
-#     st.subheader("Test Case Results")
-#     for i, test_result in enumerate(result.test_results):
-#         st.write(f"### Test Case {i + 1}")
-#         st.write(f"**Input:** {test_result.input}")  # Use dot notation
-#         st.write(f"**Expected Output:** {test_result.expected_output}")  # Use dot notation
-#         st.write(f"**Actual Output:** {test_result.actual_output}")  # Use dot notation
-#         st.write(f"**Time:** {test_result.time}")  # Use dot notation
-#         st.write(f"**Memory:** {test_result.memory}")  # Use dot notation
-#         if test_result.stderror:  # Use dot notation
-#             st.write(f"**Standard Error:** {test_result.stderror}")  # Use dot notation
-#         if test_result.compiler_errors:
-#             st.write(f"**Compiler Errors:** {test_case.compiler_errors}")
-#         st.write("---")
-
-#     st.subheader("Pipeline Metadata")
-#     st.write(f"**Total Iterations:** {result.iterations}")
-#     st.write(f"**Success:** {result.success}")
-
-#     # Display iteration history
-#     st.subheader("Iteration History")
-#     for history in result.history:
-#         # Save the iteration to the database
-#         iteration = save_iteration(
-#             question_id=question.id,
-#             iteration_number=history.iteration,
-#             chain_of_thought=history.chain_of_thought,
-#             generated_code=history.code,
-#             success=all(test_case.passed for test_case in history.test_results)
-#         )
-#         st.write(f"### Iteration {history.iteration}")
-#         st.write("**Chain of Thought:**")
-#         for i, step in enumerate(history.chain_of_thought, 1):
-#             st.write(f"{i}. {step}")
-#         st.write("**Generated Code:**")
-#         st.code(history.code, language=language_code)
-#         st.write("**Execution Result:**")
-#         st.text(history.execution_result.output)
-#         if history.execution_result.stderror:
-#             st.write(f"**Standard Error:** {history.execution_result.stderror}")
-#         if history.execution_result.compiler_errors:
-#             st.write(f"**Compiler Errors:** {history.execution_result.compiler_errors}")
-#         st.write("**Test Case Results:**")
-#         for i, test_result in enumerate(history.test_results):
-#             save_test_case_results(
-#                 iteration_id=iteration.id,
-#                 input_data=test_result.input,
-#                 expected_output=test_result.expected_output,
-#                 actual_output=test_result.actual_output,
-#                 execution_time=test_result.time,
-#                 memory_usage=test_result.memory,
-#                 stderror=test_result.stderror or "",
-#                 compiler_errors=test_result.compiler_errors or "",
-#                 passed=test_result.passed
-#             )
-#             st.write(f"#### Test Case {i + 1}")
-#             st.write(f"**Input:** {test_result.input}")
-#             st.write(f"**Expected Output:** {test_result.expected_output}")
-#             st.write(f"**Actual Output:** {test_result.actual_output}")
-#             st.write(f"**Time:** {test_result.time}")
-#             st.write(f"**Memory:** {test_result.memory}")
-#             st.write(f"**Passed:** {test_result.passed}")
-#             if test_result.stderror:
-#                 st.write(f"**Standard Error:** {test_result.stderror}")
-#             if test_result.compiler_errors:
-#                 st.write(f"**Compiler Errors:** {test_result.compiler_errors}")
-#         st.write("---")
+    uvicorn.run(app, host="0.0.0.0", port=8000, reload=True)

backend/src/models.py

@@ -1,5 +1,5 @@
 from pydantic import BaseModel, Field
-from typing import List, Dict, Any, Optional
+from typing import List, Optional
 
 class TestCaseResult(BaseModel):
     input: str = Field(description="Input for the test case")
@@ -39,4 +39,15 @@ class PipelineResult(BaseModel):
     test_results: List[TestCaseResult] = Field(description="Results of test case validation")
     iterations: int = Field(description="Total number of iterations")
     history: List[CodeIterationHistory] = Field(description="History of all iterations")
-    success: bool = Field(description="Whether the pipeline was successful")
+    success: bool = Field(description="Whether the pipeline was successful")
+
+class PipelineRequest(BaseModel):
+    model: str
+    language: str
+    question: str
+    explanation: Optional[str] = None
+    user_input: Optional[str] = None
+    max_iterations: int = 3
+    generate_test_cases: bool = True
+    test_cases: Optional[List[TestCase]] = []
+    api_key: str