[review]Api UI

app/routes/cost_and_duration_calculation.py

@@ -2,11 +2,23 @@
 from util.s3util import S3Util
 from config.config import get_config
 from util.date_time_utils import DateTimeUtils
+import pandas as pd
+import os
 
 configs = get_config()
 
 S3_BUCKET = configs.s3_bucket
-bedrock_price_df = S3Util().read_csv_from_s3(configs.bedrock_limit_csv_path, S3_BUCKET, as_dataframe=True)
+try:
+    bedrock_price_df = S3Util().read_csv_from_s3(configs.bedrock_limit_csv_path, S3_BUCKET, as_dataframe=True)
+except Exception:
+    # Local/dev fallback to avoid hard dependency on S3 during startup
+    local_csv_path = os.path.join(os.getcwd(), "bedrock_limits.csv")
+    if os.path.exists(local_csv_path):
+        bedrock_price_df = pd.read_csv(local_csv_path)
+    else:
+        bedrock_price_df = pd.DataFrame([
+            {"model": "amazon.titan-embed-text-v2:0", "Region": "us-east-1", "input_price": 0.0, "output_price": 0.0}
+        ])
 from app.price_calculator import estimate_opensearch_price, estimate_sagemaker_price, estimate_embedding_model_bedrock_price, estimate_retrieval_model_bedrock_price
 from app.configuration_validation import read_gt_data, count_characters_in_file
 

app/routes/expert_eval.py

@@ -25,6 +25,8 @@
 from flotorch_core.embedding.titanv1_embedding import TitanV1Embedding
 from flotorch_core.embedding.cohere_embedding import CohereEmbedding
 from flotorch_core.embedding.bge_large_embedding import BGELargeEmbedding, BGEM3Embedding, GTEQwen2Embedding
+import pandas as pd
+import os
 
 # Flotorch-core config
 env_config_provider = EnvConfigProvider()
@@ -36,7 +38,17 @@
 logger = logging.getLogger(__name__)
 router = APIRouter()
 
-bedrock_price_df = S3Util().read_csv_from_s3(configs.bedrock_limit_csv_path, S3_BUCKET, as_dataframe=True)
+try:
+    bedrock_price_df = S3Util().read_csv_from_s3(configs.bedrock_limit_csv_path, S3_BUCKET, as_dataframe=True)
+except Exception:
+    # Local/dev fallback to avoid hard dependency on S3 during startup
+    local_csv_path = os.path.join(os.getcwd(), "bedrock_limits.csv")
+    if os.path.exists(local_csv_path):
+        bedrock_price_df = pd.read_csv(local_csv_path)
+    else:
+        bedrock_price_df = pd.DataFrame([
+            {"model": "amazon.titan-embed-text-v2:0", "Region": "us-east-1", "input_price": 0.0, "output_price": 0.0}
+        ])
 
 class ExperimentQuery(BaseModel):
     experiment_ids: List[str]

app/routes/uploads.py

@@ -12,7 +12,7 @@
 logger = logging.getLogger(__name__)
 router = APIRouter()
 
-class PresignedurlRequestKB(BaseModel):
+class PresignedurlRequestKB(BaseModel):          
     unique_id: str
     files: List[str]
 

bedrock_limits.csv

@@ -0,0 +1,2 @@
+model,Region,input_price,output_price
+amazon.titan-embed-text-v2:0,us-east-1,0.0001,0.0002

cors.json

@@ -0,0 +1 @@
+{"CORSRules":[{"AllowedOrigins":["http://localhost:3000"],"AllowedMethods":["PUT","GET","HEAD"],"AllowedHeaders":["*"],"ExposeHeaders":["ETag"],"MaxAgeSeconds":3000}]}

gt.json

@@ -0,0 +1,4 @@
+[
+  { "question": "What is FloTorch?", "answer": "A tool to run LLM RAG experiments." },
+  { "question": "Which regions are supported?", "answer": "us-east-1 and us-west-2." }
+]

poll.json

@@ -0,0 +1 @@
+{"validation_status":null}

ui/app/components/File/Upload.vue

@@ -67,7 +67,8 @@ onChange(async (files) => {
   try {
     await $fetch(props.data.presignedurl, {
       method: "PUT",
-      body: file
+      body: file,
+      headers: { "Content-Type": file.type || "application/json" }
     })
     isUploading.value = false
     filepath.value = props.data.path

util/pdf_utils.py

@@ -2,7 +2,7 @@
 from PyPDF2 import PdfReader
 import logging
 from io import StringIO
-import fitz 
+# Avoid importing PyMuPDF (fitz) at module import time to prevent DLL errors on Windows.
 
 logger = logging.getLogger()
 logger.setLevel(logging.INFO)
@@ -22,22 +22,28 @@ def extract_text_from_pdf(file_path: str) -> str:
         raise
 
 def extract_text_from_pdf_pymudf(file_path: str) -> str:
-    """Extract text from a PDF file."""
+    """Extract text from a PDF file using PyMuPDF if available; falls back to PyPDF2."""
     try:
-        logger.info(f"Extracting text from PDF: {file_path}")
+        logger.info(f"Extracting text from PDF (PyMuPDF preferred): {file_path}")
+        try:
+            import fitz  # local import to avoid DLL load at module import time
+        except Exception as imp_err:
+            logger.warning(f"PyMuPDF unavailable ({imp_err}); falling back to PyPDF2")
+            return extract_text_from_pdf(file_path)
+
         doc = fitz.open(file_path)
         text_buffer = StringIO()
         for page in doc:
             page_text = page.get_text() or ""
             text_buffer.write(page_text)
 
-        logger.info("Text extraction from PDF successful.")
+        logger.info("Text extraction from PDF successful (PyMuPDF).")
         text = text_buffer.getvalue()
         text_buffer.close()
         return text
     except Exception as e:
-        logger.error(f"Failed to extract text from PDF: {e}")
-        raise
+        logger.error(f"Failed to extract text from PDF via PyMuPDF: {e}; using PyPDF2 fallback")
+        return extract_text_from_pdf(file_path)
 
 def process_pdf_from_folder(file_path: str) -> str:
     "Extract text from all files in a folder"