Krishna172912 commited on
Commit
6d4062f
Β·
1 Parent(s): 38105c3

Minor Bugs Fixed

Browse files
back_end/config.py CHANGED
@@ -364,4 +364,4 @@ SUPERVISOR_SYSTEM_PROMPT = """
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  """
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- MAX_FILES_TO_CREATE_VECTOR_DB = 6000
 
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  """
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+ MAX_FILES_TO_CREATE_VECTOR_DB = 6000
back_end/core/embeddings.py CHANGED
@@ -28,10 +28,7 @@ class _SFRCodeEmbeddings(Embeddings):
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  def __init__(self, model_path='Salesforce/SFR-Embedding-Code-400M_R'):
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  print("Loading local SFR Code Model to GPU via ST...")
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- #self.model = SentenceTransformer(model_path, device='cuda', trust_remote_code=True)
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- # Automatically detect the hardware
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- hardware_device = "cuda" if torch.cuda.is_available() else "cpu"
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- self.model = SentenceTransformer(model_path, device=hardware_device, trust_remote_code=True)
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  self.model.max_seq_length = 1024
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  self.model[0].auto_model.register_forward_pre_hook(_inject_position_ids_hook, with_kwargs=True)
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@@ -115,4 +112,4 @@ def get_vector_db() -> Chroma:
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  embedding_function=local_embedding_fn,
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  collection_name=CHROMA_COLLECTION_NAME,
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  )
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- return vector_db
 
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  def __init__(self, model_path='Salesforce/SFR-Embedding-Code-400M_R'):
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  print("Loading local SFR Code Model to GPU via ST...")
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+ self.model = SentenceTransformer(model_path, device='cuda', trust_remote_code=True)
 
 
 
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  self.model.max_seq_length = 1024
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  self.model[0].auto_model.register_forward_pre_hook(_inject_position_ids_hook, with_kwargs=True)
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  embedding_function=local_embedding_fn,
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  collection_name=CHROMA_COLLECTION_NAME,
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  )
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+ return vector_db
back_end/core/splitter.py CHANGED
@@ -193,4 +193,4 @@ def custom_splitter(docs: List[Document],current_dir: Path) -> List[Document]:
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  print(f"Original Files Processed : {len(docs)}")
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  print(f"Total Chunks Generated : {len(all_chunks)}")
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- return all_chunks
 
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  print(f"Original Files Processed : {len(docs)}")
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  print(f"Total Chunks Generated : {len(all_chunks)}")
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+ return all_chunks
back_end/main.py CHANGED
@@ -1,5 +1,4 @@
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  # main.py
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- from fastapi.staticfiles import StaticFiles
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  from fastapi import FastAPI
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  from fastapi.responses import StreamingResponse
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  from fastapi.middleware.cors import CORSMiddleware
@@ -190,11 +189,4 @@ async def chat_stream(request: ChatRequest):
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  yield format_chat_chunk("end", "[END]")
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  await asyncio.sleep(0.01)
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- return StreamingResponse(generate_response(), media_type="text/event-stream")
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-
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- # 1. Find the path to the front_end folder
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- current_dir = os.path.dirname(os.path.abspath(__file__))
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- frontend_dir = os.path.join(current_dir, "..", "front_end")
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-
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- # 2. Tell FastAPI to serve your index.html when people visit the main URL
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- app.mount("/", StaticFiles(directory=frontend_dir, html=True), name="frontend")
 
1
  # main.py
 
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  from fastapi import FastAPI
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  from fastapi.responses import StreamingResponse
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  from fastapi.middleware.cors import CORSMiddleware
 
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  yield format_chat_chunk("end", "[END]")
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  await asyncio.sleep(0.01)
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+ return StreamingResponse(generate_response(), media_type="text/event-stream")
 
 
 
 
 
 
 
front_end/app.js CHANGED
@@ -138,8 +138,7 @@ function startAnalysis() {
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  // ─────────────────────────────────────────────
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  async function connectToBackend(repoUrl) {
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  try {
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- //const response = await fetch('http://localhost:8000/init-repo', {
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- const response = await fetch('/init-repo', {
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  method: 'POST',
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  headers: { 'Content-Type': 'application/json' },
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  body: JSON.stringify({ url: repoUrl }),
@@ -418,8 +417,7 @@ async function sendMessage() {
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  let fullMarkdown = '';
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420
  try {
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- //const response = await fetch('http://localhost:8000/chat', {
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- const response = await fetch('/chat', {
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  method: 'POST',
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  headers: { 'Content-Type': 'application/json' },
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  body: JSON.stringify({ message: text }),
 
138
  // ─────────────────────────────────────────────
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  async function connectToBackend(repoUrl) {
140
  try {
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+ const response = await fetch('http://localhost:8000/init-repo', {
 
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  method: 'POST',
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  headers: { 'Content-Type': 'application/json' },
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  body: JSON.stringify({ url: repoUrl }),
 
417
  let fullMarkdown = '';
418
 
419
  try {
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+ const response = await fetch('http://localhost:8000/chat', {
 
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  method: 'POST',
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  headers: { 'Content-Type': 'application/json' },
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  body: JSON.stringify({ message: text }),