Update app.py

app.py

@@ -1,8 +1,87 @@
+
+from langchain.llms import CTransformers
 from langchain.agents import Tool
 from langchain.chains import RetrievalQA
 from langchain.text_splitter import CharacterTextSplitter
 from langchain_community.document_loaders import PyPDFLoader
 from langchain_community.vectorstores import FAISS
+from langchain.embeddings import HuggingFaceBgeEmbeddings
 import streamlit as st
 
-st.title("Docuverse")
+
+def main():
+
+    FILE_LOADER_MAPPING = {
+    "pdf": (PyPDFLoader, {})
+    # Add more mappings for other file extensions and loaders as needed
+    }
+
+    st.title("Document Comparison with Q&A using Agents")
+    
+    config = {
+    'max_new_tokens': 1024,
+    'repetition_penalty': 1.1,
+    'temperature': 0.1,
+    'top_k': 50,
+    'top_p': 0.9,
+    'stream': True,
+    'threads': int(os.cpu_count() / 2)
+    }
+    
+    llm = CTransformers(
+        model="TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF",
+        model_file="mistral-7b-instruct-v0.2.Q4_0.gguf",
+        model_type="mistral",
+        lib="avx2", #for CPU use
+        **config
+    )
+    
+    print("LLM Initialized...")
+    
+    
+    
+    model_name = "BAAI/bge-large-en"
+    model_kwargs = {'device': 'cpu'}
+    encode_kwargs = {'normalize_embeddings': False}
+    embeddings = HuggingFaceBgeEmbeddings(
+        model_name=model_name,
+        model_kwargs=model_kwargs,
+        encode_kwargs=encode_kwargs
+    )
+
+    # Upload files
+    uploaded_files = st.file_uploader("Upload your documents", type=["pdf], accept_multiple_files=True)
+    loaded_documents = []
+
+    if uploaded_files:
+        # Create a temporary directory
+        with tempfile.TemporaryDirectory() as td:
+            # Move the uploaded files to the temporary directory and process them
+            for uploaded_file in uploaded_files:
+                st.write(f"Uploaded: {uploaded_file.name}")
+                ext = os.path.splitext(uploaded_file.name)[-1][1:].lower()
+                st.write(f"Uploaded: {ext}")
+
+                # Check if the extension is in FILE_LOADER_MAPPING
+                if ext in FILE_LOADER_MAPPING:
+                    loader_class, loader_args = FILE_LOADER_MAPPING[ext]
+                    # st.write(f"loader_class: {loader_class}")
+
+                    # Save the uploaded file to the temporary directory
+                    file_path = os.path.join(td, uploaded_file.name)
+                    with open(file_path, 'wb') as temp_file:
+                        temp_file.write(uploaded_file.read())
+
+                    # Use Langchain loader to process the file
+                    loader = loader_class(file_path, **loader_args)
+                    loaded_documents.extend(loader.load())
+                else:
+                    st.warning(f"Unsupported file extension: {ext}")
+
+    
+
+
+
+if __name__ == "__main__":
+    main()
+