added the huggingface code and updated reddit integration with autogen

_integrations/reddit/main.py

@@ -0,0 +1,73 @@
+import streamlit as st
+import json
+import reddit
+
+st.title = "Reddit App"
+
+with st.container(border=True):
+    mode = st.radio(
+        "Choose a mode",
+        [":rainbow[Random]", "***Specific Subreddit***"],
+        captions=["Laugh out loud.", "Get the popcorn."]
+    )
+
+    number = st.slider("Pick a number", 1, 10)
+
+    response = ""
+
+    if mode == ":rainbow[Random]":
+        prompt = f"Get me {number} random subreddit(s)!"
+        submit = st.button(prompt)
+
+        if submit:
+            response = reddit.start_chat(prompt)
+
+    if mode == "***Specific Subreddit***":
+        input = st.text_input("")
+        submit = st.button(f"Give me content!")
+        prompt = f"Give me {number} subreddit posts on: {input}"
+
+        if submit:
+            response = reddit.start_chat(prompt)
+
+with st.spinner('Wait for it...'):
+    if response:
+        st.success('Done!')
+        response = json.loads(response)
+        st.divider()
+
+        for data in response:
+            # Extracting 'content'
+            content = data["content"]
+
+            # Extracting 'meta_data'
+            meta_data = data["meta_data"]
+
+            # Extracting each property from 'meta_data'
+            post_subreddit = meta_data["subreddit"]
+            post_category = meta_data["category"]
+            post_title = meta_data["title"]
+            post_score = meta_data["score"]
+            post_url = meta_data["url"]
+            post_author = meta_data["author"]
+
+            st.header("Metadata")
+            st.divider()
+            st.markdown('**Subreddit**: ' + post_subreddit)
+            st.markdown('**Category**: ' + post_category)
+            st.markdown('**Title**: ' + post_title)
+            st.markdown('**URL**: ' + post_url)
+            st.markdown('**Author**: ' + post_author)
+
+            st.header("Content")
+            st.divider()
+            st.write(content)
+
+
+
+
+
+
+
+
+

_integrations/reddit/reddit.py

@@ -5,7 +5,7 @@
 from dotenv import load_dotenv
 from typing_extensions import Annotated
 
-from _integrations.reddit.reddit_classes import RedditPostsLoader
+from reddit_classes import RedditPostsLoader
 
 load_dotenv()
 
@@ -30,7 +30,7 @@
 
 user_proxy = autogen.UserProxyAgent(
     name="Admin",
-    human_input_mode="ALWAYS",
+    human_input_mode="NEVER",
     code_execution_config=False,
 )
 
@@ -45,7 +45,7 @@ def get_random_subreddit(
         client_id=os.getenv("CLIENT_ID"),
         client_secret=os.getenv("CLIENT_SECRET"),
         user_agent="extractor by u/tyler_programming",
-        categories=["new", "hot"],
+        categories=["hot"],
         mode=mode,
         number_posts=number_of_posts,
     )
@@ -58,7 +58,7 @@ def get_random_subreddit(
 
 
 @user_proxy.register_for_execution()
-@engineer.register_for_llm(description="Get a random subreddit")
+@engineer.register_for_llm(description="Get a specified subreddit")
 def get_specified_subreddit(
         search_queries: Annotated[str, "The search queries comma separated"],
         number_of_posts: Annotated[int, "The number of posts to retrieve, default should be 1"]
@@ -82,24 +82,46 @@ def get_specified_subreddit(
     return serialized_data
 
 
-chat_result = user_proxy.initiate_chat(
-    engineer,
-    message="""
-        I need you to integrate with Reddit.  Whenever you retrieve a post, you will get a RedditReader Object list and
-        I would like you to format the content and meta_data contained within.
-        
-        Metadata is in this format for each item in the list:
-        
-        reddit_list.post_subreddit,
-        reddit_list.post_category,
-        reddit_list.post_title,
-        reddit_list.post_score,
-        reddit_list.post_id,
-        reddit_list.post_url,
-        reddit_list.post_author
-        
-        Then also add the content from the item.
-        
-        Do not start until I give a command.
-""",
-)
+def start_chat(input: str):
+    chat_result = user_proxy.initiate_chat(
+        engineer,
+        max_turns=2,
+        message=f"""
+            I need you to integrate with Reddit.  Whenever you retrieve a post, you will get a RedditReader Object list and
+            I would like you to format the content and meta_data contained within.
+            
+            Metadata is in this format for each item in the list:
+            
+            reddit_list.post_subreddit,
+            reddit_list.post_category,
+            reddit_list.post_title,
+            reddit_list.post_score,
+            reddit_list.post_id,
+            reddit_list.post_url,
+            reddit_list.post_author
+            
+            Then also add the content from the item.
+            
+            Return this in proper json format, do not use triple tick marks to denote that it's json.  If there is more 
+            than 1 object, make sure it's an array.
+            
+        [
+            {{
+        "meta_data": {{
+            "subreddit": the subreddit,
+            "category": the category,
+            "title": the title,
+            "score": the score,
+            "post_id": the post id,
+            "url": the url,
+            "author": the author
+            }},
+            "content": the content
+            }}
+        ]
+            
+        {input}
+    """,
+    )
+
+    return chat_result.summary

huggingface/llama.py

@@ -0,0 +1,17 @@
+import requests
+import pprint as p
+
+API_URL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct"
+headers = {"Authorization": "Bearer hf_xxxx"}
+
+
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
+
+
+output = query({
+    "inputs": "Can you give me a sample python function for binary search.",
+})
+
+p.pprint(output)

huggingface/main.py

@@ -0,0 +1,20 @@
+import requests
+
+API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
+headers = {"Authorization": "Bearer hf_xxxx"}
+
+
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.content
+
+
+image_bytes = query({
+    "inputs": "Astronaut riding a horse",
+})
+# You can access the image with PIL.Image for example
+import io
+from PIL import Image
+
+image = Image.open(io.BytesIO(image_bytes))
+image.save("tester.png")