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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+recording0.wav filter=lfs diff=lfs merge=lfs -text

audio-to-text.py

@@ -0,0 +1,101 @@
+import os
+import streamlit as st
+import whisper
+from dotenv import load_dotenv
+from langchain.chains import RetrievalQA
+from audiorecorder import audiorecorder
+from langchain.document_loaders import DirectoryLoader
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores.faiss import FAISS
+from langchain.chat_models import ChatOpenAI
+
+load_dotenv()
+
+api_key = os.getenv("OPENAI_API_KEY")
+
+st.title("Avtarcoach Audio-to-text")
+
+# audio_bytes = audio_recorder("Click to record", "Click to stop recording", neutral_color="#051082", icon_size="2x")
+# if audio_bytes:
+#     st.audio(audio_bytes, format="audio/wav")
+
+audio = audiorecorder("Click to record", "Click to stop recording")
+
+if len(audio) > 0:
+    # To play audio in frontend:
+    st.audio(audio.export().read())
+
+    # To save audio to a file, use pydub export method:
+    audio.export("audio.wav", format="wav")
+
+    # To get audio properties, use pydub AudioSegment properties:
+    st.write(
+        f"Frame rate: {audio.frame_rate}, Frame width: {audio.frame_width}, Duration: {audio.duration_seconds} seconds")
+
+model = whisper.load_model("base")
+
+# load audio and pad/trim it to fit 30 seconds
+audio = whisper.load_audio(r"audio.wav")
+audio = whisper.pad_or_trim(audio)
+
+# make log-Mel spectrogram and move to the same device as the model
+mel = whisper.log_mel_spectrogram(audio).to(model.device)
+
+# detect the spoken language
+_, probs = model.detect_language(mel)
+st.write(f"Detected language: {max(probs, key=probs.get)}")
+
+# decode the audio
+options = whisper.DecodingOptions(fp16=False)
+result = whisper.decode(model, mel, options)
+
+# print the recognized text
+st.write("You Said: ", result.text)
+input_text = result.text
+
+st.markdown("""<hr style="height:10px;border:none;color:#333;background-color:#333;" /> """, unsafe_allow_html=True)
+
+st.write("Avtarcoach Response: ")
+
+# Gen AI results
+
+pdf_loader = DirectoryLoader(
+    r'C:\Users\shpe1\Downloads\tea_project_text_to_text-main\tea_project_text_to_text-main\pdf_docs', glob="**/*.pdf",
+    use_multithreading=True)
+docs_loader = DirectoryLoader(
+    r'C:\Users\shpe1\Downloads\tea_project_text_to_text-main\tea_project_text_to_text-main\docs', glob="**/*.docx",
+    use_multithreading=True)
+csv_loader = DirectoryLoader(
+    r'C:\Users\shpe1\Downloads\tea_project_text_to_text-main\tea_project_text_to_text-main\docs', glob="**/*.csv",
+    use_multithreading=True)
+xlsx_loader = DirectoryLoader(
+    r'C:\Users\shpe1\Downloads\tea_project_text_to_text-main\tea_project_text_to_text-main\docs', glob="**/*.xlsx",
+    use_multithreading=True)
+loaders = [pdf_loader, docs_loader, csv_loader, xlsx_loader]
+
+documents = []
+for loader in loaders:
+    documents.extend(loader.load())
+
+text_splitters = RecursiveCharacterTextSplitter(
+    chunk_size=2000,
+    chunk_overlap=200,
+    length_function=len
+)
+
+chunks = text_splitters.split_documents(documents)
+embedding = OpenAIEmbeddings()
+# db = FAISS.from_documents(chunks, embedding)
+faiss_db = FAISS.from_documents(chunks, embedding)
+retriever = faiss_db.as_retriever(search_type='mmr')
+llm = ChatOpenAI(model="gpt-4-1106-preview", temperature=0)
+qa_chain = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever)
+
+# doc_search =faiss_db.get_relevant_documents(input_text)
+# llm = ChatOpenAI(model="gpt-4-1106-preview",temperature =0)
+# qa_chain = load_qa_chain(llm=llm,chain_type="stuff")
+# qa_document_chain = AnalyzeDocumentChain(combine_docs_chain=qa_chain)
+response = qa_chain.run(input_text)
+
+st.write(response)

recording0.wav

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4ef40337ebb5b111c40947a994d0ea0ef0412e27623e8fe6353b316208db255d
+size 5760058