Upload 35 files

app_drive.py

@@ -11,8 +11,9 @@ from driveapi.drive_database import create_chroma_db
 
 # global time_diff, model_name, search_type
 time_diff = 0
-# model_name="gpt-3.5-turbo-1106"
-model_name = "gpt-4-1106-preview"
+model_name="gpt-3.5-turbo-1106"
+# model_name = "gpt-4-1106-preview"
+# model_name = "gpt-4-0125-preview"
 search_type = "stuff"
 input_question = ""
 model_response = ""
@@ -83,12 +84,15 @@ def save_feedback(feedback):
         ["Question", "Response", "Model", "Time", "Feedback"],
         [input_question, model_response, model_name, time_diff, user_feedback]
     ]
-
-    if user_feedback != "🤔":
+    
+    if user_feedback[0] != "None":
         upload_chat_to_drive(log_data, file_name)
 
 def default_feedback():
-    return "🤔"
+    return "None"
+
+def default_text():
+    return ""
 
 def text_feedback(feedback):
     global text_feedback
@@ -145,10 +149,10 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald", neutral_hue="slate"))
     with gr.Row():
         with gr.Column():
             feedback_radio = gr.Radio(
-                choices=["1", "2", "3", "4", "5", "6", "🤔"],
-                value=["🤔"],
+                choices=["1", "2", "3", "4", "5", "6", "None"],
+                value=["None"],
                 label="How would you rate the current response?",
-                info="Choosing a number sends the following diagnostic data to the developer - Question, Response, Time Taken. Let it be 🤔 to not send any data.",
+                info="Choosing a number sends the following diagnostic data to the developer - Question, Response, Time Taken. Let it be [None] to not send any data.",
             )
         
         with gr.Column():
@@ -157,7 +161,7 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald", neutral_hue="slate"))
 
     msg.submit(respond, [msg, chatbot], [msg, chatbot])
     msg.submit(default_feedback, outputs=[feedback_radio])
-    
+    msg.submit(default_text, outputs=[feedback_text])
 
     feedback_radio.change(
         fn=save_feedback,

driveapi/service.py

@@ -6,6 +6,7 @@ def get_credentials():
     private_key = os.environ.get('GOOGLE_PRIVATE_KEY').replace('\\n', '\n')
     token_uri = os.environ.get('GOOGLE_TOKEN_URI')
 
+
     # Create credentials object
     credentials_info = {
         'type': 'service_account',

lc_base/README_BASE.md

@@ -0,0 +1,78 @@
+# ChatLLMs
+Gradio Interface for LLM-Powered PDF Chats
+
+This chatbot is designed to provide intelligent responses and answers to questions based on the content of PDF documents.Leverages [Gradio](https://www.gradio.app/) as a user-friendly interface to engage with chatbots powered by [OpenAI](https://openai.com/) models based on [langchain](https://www.langchain.com/). Additionally, it incorporates [ChromaDB](https://www.trychroma.com/) for efficient data storage.
+
+Current LLM used - GPT4-1106-preview
+
+A base interface demo is available on this [HF space](https://huggingface.co/spaces/Koshti10/Chat_literature) for testing 
+
+## Getting started
+
+Clone this repository and add your OpenAI API key in local environment
+
+```python
+git clone https://github.com/kushal-10/chatllms
+cd chatllms
+export OPENAI_API_KEY = <your secret key>
+```
+
+Install required dependencies
+```python
+pip install -r requirements.txt
+```
+
+## Usage
+
+### Chatting over all the given documents, using stuff to iterate over 100 most relevant documents
+
+Step 1: 
+
+Create a new folder under `inputs`, for example `new_docs`, and add your PDFs here. 
+
+Step 2:
+Specify this as `inp_dir` in `save_db.py` and additionally specify where you would like the Chroma database to be stored in `out_dir`.Then run
+
+```python
+python3 lc_base/save_db.py
+```
+
+Step 3:
+Specify the `out_dir` in `app.py` along with additional parameters and then run `app.py` to run the gradio interface locally.
+```
+python3 app.py
+```
+
+Add the API key and chat away!!
+
+### Chatting over summaries of all given documents using map_reduce.
+
+Step 1: 
+
+Create a new folder under `inputs`, for example `new_docs`, and add your PDFs here. 
+
+Step 2:
+Specify this as `inpur_dir` in `main.py` and additionally specify in which folder you would like the individual Chroma database to be stored in `output_dir`. Also specify where you would like to save combined database of summaries. Change other params if required. Then run
+
+```python
+python3 main.py
+```
+
+Step 3:
+Specify the `output_dir` in `app.py` along with additional parameters and then run `app.py` to run the gradio interface locally.
+```
+python3 app.py
+```
+
+Add the API key and chat away!!
+
+All the responses will be saved in csv files under logs folder
+
+
+
+
+
+
+
+
+

outputs/combined/policy_eu_asia_usa/faiss_index/index.faiss

@@ -1,3 +1,3 @@
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 size 7391277

outputs/combined/policy_eu_asia_usa/faiss_index/index.pkl

@@ -1,3 +1,3 @@
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+oid sha256:970472b3e8de040d6d6136dc8658bf6d94b23c30a581f28a541d79458b6f6aa8
 size 1285422

requirements.txt

@@ -7,4 +7,4 @@ openai==0.28.1
 langchain==0.0.331
 google-auth 
 google-auth-httplib2 
-google-api-python-client
+google-api-python-client