Upload 2 files

app.py

@@ -0,0 +1,79 @@
+import streamlit as st
+from lida import Manager, TextGenerationConfig, llm
+from dotenv import load_dotenv
+import os
+import io
+from PIL import Image
+from io import BytesIO
+import base64
+
+HUGGINGFACE_API_TOKEN = os.environ.get('HF_TOKEN')
+
+def base64_to_image(base64_string):
+
+    byte_data = base64.b64decode(base64_string)
+
+    return Image.open(BytesIO(byte_data))
+
+
+
+#from LIDA github
+text_gen = llm(model="uukuguy/speechless-llama2-hermes-orca-platypus-13b", device_map="auto")
+
+lida = Manager(text_gen=text_gen)
+
+
+
+
+textgen_config = TextGenerationConfig(n=1, temperature=0.1, max_tokens=512)
+
+
+menu = st.sidebar.selectbox("Summary or Query", ["Summary", "Query"])
+
+if menu == "Summary":
+    st.subheader("Summarization of the Data")
+    file_uploader = st.file_uploader("Upload your file", type="csv")
+    if file_uploader is not None:
+        path_to_save = "filename.csv"
+        with open(path_to_save, "wb") as f:
+            f.write(file_uploader.getvalue())
+        summary = lida.summarize("filename.csv", summary_method="default")
+        st.write(summary)
+        goals = lida.goals(summary, n=2, textgen_config=textgen_config)
+        for goal in goals:
+            st.write(goal)
+        i = 0
+        library = "seaborn"
+        text_gen_config = TextGenerationConfig(n=1, temperature=0.1, use_cache=True)
+        charts = lida.visualize(summary=summary, goal=goals[i], textgen_config=textgen_config, library=library)
+        img_base64_string = charts[0].raster
+        img = base64_to_image(img_base64_string)
+        st.image(img)
+
+elif menu == "Query":
+    st.subheader("Questioning of the Data")
+    file_uploader = st.file_uploader("Upload your file", type="csv")
+    if file_uploader is not None:
+        path_to_save = "filename1.csv"
+        with open(path_to_save, "wb") as f:
+            f.write(file_uploader.getvalue())
+
+        text_area = st.text_area("Query your data to generate visualization", height=200)
+        if st.button("Generate Graph"):
+            if len(text_area) > 0:
+                # st.info("Your query " + text_area)
+                # lida = Manager(text_gen=text_gen)
+                # text_gen_config = TextGenerationConfig(n=1, temperature=0.1, use_cache=True)
+                summary = lida.summarize("filename1.csv", summary_method="default", textgen_config=textgen_config)
+                user_query = text_area
+                charts = lida.visualize(summary=summary, goal=user_query, textgen_config=textgen_config)
+                img_base64_string = charts[0].raster
+                img = base64_to_image(img_base64_string)
+                st.image(img)
+                charts[0]
+
+
+
+
+
+

requirements.txt

@@ -0,0 +1,4 @@
+lida
+lida[transformers]
+torch
+streamlit