push to origin

.gitignore

@@ -0,0 +1,5 @@
+fplenv/
+.DS_Store
+.env
+
+__pycache__/

README.md

@@ -10,4 +10,39 @@ pinned: false
 license: mit
 ---
 
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+
+# FPL Chatbot
+
+This is a chatbot that interacts with the Fantasy Premier League (FPL) API to provide information about players, teams, and stats.
+
+```bash
+python3 -m venv fplenv  
+source fplenv/bin/activate
+
+```
+
+## Installation
+
+1. Clone the repository:
+
+    ```bash
+    git clone https://github.com/yourusername/fpl_chatbot.git
+    cd fplChatbot
+    ```
+
+2. Install the dependencies:
+
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+3. Run the chatbot:
+
+    ```bash
+    python app.py
+    ```
+
+## Usage
+
+- Ask about a player's stats: "Tell me about Harry Kane's stats."
+- Ask about a team: "Show me all players from Manchester United."

app.py

@@ -1,63 +1,15 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from fpl_client import FPLClient
+from nlp_utils import process_query
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# Initialize the FPL client
+fpl_client = FPLClient()
 
+# Function to handle user input and generate a response
+def chatbot_response(query):
+    response = process_query(query, fpl_client)
+    return response
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()
+# Set up the Gradio interface
+iface = gr.Interface(fn=chatbot_response, inputs="text", outputs="text", title="FPL Chatbot")
+iface.launch()

fpl_client.py

@@ -0,0 +1,75 @@
+import requests
+import logging
+
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+class FPLClient:
+    def __init__(self):
+        self.base_url = "https://fantasy.premierleague.com/api"
+        self.data = self.get_static_data()
+
+    def get_static_data(self):
+        url = f"{self.base_url}/bootstrap-static/"
+        logging.info(f"Fetching static data from {url}")
+        response = requests.get(url)
+        if response.status_code == 200:
+            logging.debug("Static data fetched successfully.")
+            return response.json()
+        else:
+            logging.error(f"Failed to fetch static data. Status code: {response.status_code}")
+            return None
+
+    def get_teams(self):
+        teams = self.data.get('teams', [])
+        logging.info(f"Fetching team names. Total teams: {len(teams)}")
+        return [team['name'] for team in teams]
+    
+    def get_player_info(self, player_name):
+        logging.info(f"Searching for player: {player_name}")
+        players = self.data['elements']
+        player = next((p for p in players if p['web_name'].lower() == player_name.lower()), None)
+        if player:
+            logging.debug(f"Player found: {player['web_name']}")
+        else:
+            logging.warning(f"Player not found: {player_name}")
+        return player
+
+    def get_team_info(self, team_id):
+        logging.info(f"Fetching team info for team ID: {team_id}")
+        teams = self.data['teams']
+        team = next((t for t in teams if t['id'] == team_id), None)
+        if team:
+            logging.debug(f"Team found: {team['name']}")
+        else:
+            logging.warning(f"Team not found for ID: {team_id}")
+        return team
+
+    def get_player_stats(self, player_name):
+        logging.info(f"Fetching stats for player: {player_name}")
+        player = self.get_player_info(player_name)
+        if player:
+            team_name = self.get_team_info(player['team'])['name']
+            stats = {
+                "Name": player['web_name'],
+                "Team": team_name,
+                "Total Points": player['total_points'],
+                "Price": player['now_cost'] / 10,
+                "Position": player['element_type'],
+                "Selected By": player['selected_by_percent'],
+            }
+            logging.debug(f"Stats for player {player_name}: {stats}")
+            return stats
+        logging.warning(f"Stats not found for player: {player_name}")
+        return "Player not found"
+
+    def get_team_players(self, team_name):
+        logging.info(f"Fetching players for team: {team_name}")
+        teams = self.data['teams']
+        team = next((t for t in teams if t['name'].lower() == team_name.lower()), None)
+        if team:
+            players = [p['web_name'] for p in self.data['elements'] if p['team'] == team['id']]
+            logging.debug(f"Players found for team {team_name}: {players}")
+            return players
+        logging.warning(f"Team not found: {team_name}")
+        return "Team not found"

nlp_utils.py

@@ -0,0 +1,40 @@
+import re
+from fpl_client import FPLClient
+import logging
+
+# Initialize the FPL client
+fpl_client = FPLClient()
+
+# Get the list of teams
+teams = fpl_client.get_teams()
+
+def extract_player_name(query):
+    # Simple regex example to extract player names (can be enhanced)
+    match = re.search(r"(\b[A-Z][a-z]+(?:\s[A-Z][a-z]+)?)", query)
+    return match.group(1) if match else None
+
+def extract_team_name(query):
+    logging.info(f"Extracting team name from query: {query}")
+    logging.info(f"Teams: {teams}")
+    # Add your logic to extract team names, could use a list of teams
+    for team in teams:
+        if team.lower() in query.lower():
+            return team
+    return None
+
+def process_query(query, fpl_client):
+    if "stats" in query.lower():
+        player_name = extract_player_name(query)
+        if player_name:
+            stats = fpl_client.get_player_stats(player_name)
+            return stats
+        return "Player name not found in the query."
+    
+    if "team" in query.lower():
+        team_name = extract_team_name(query)
+        if team_name:
+            players = fpl_client.get_team_players(team_name)
+            return f"Players from {team_name}: {', '.join(players)}"
+        return "Team name not found in the query, please use from the list: " + ", ".join(teams)
+    
+    return "I'm not sure how to help with that."

requirements.txt

@@ -1 +1,4 @@
-huggingface_hub==0.22.2
+huggingface_hub==0.22.2
+gradio
+requests
+transformers