Merge pull request #3630 from paneru-rajan/Issue-2407-auto-update-pricing

Added script for auto updating the pricing with the pricings of openrouter.ai

.github/workflows/auto_update_price_and_context_window.yml

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+name: Updates model_prices_and_context_window.json and Create Pull Request
+
+on:
+  schedule:
+    - cron: "0 0 * * 0"  # Run every Sundays at midnight
+    #- cron: "0 0 * * *" # Run daily at midnight
+
+jobs:
+  auto_update_price_and_context_window:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - name: Install Dependencies
+        run: |
+          pip install aiohttp
+      - name: Update JSON Data
+        run: |
+          python ".github/workflows/auto_update_price_and_context_window_file.py"
+      - name: Create Pull Request
+        run: |
+          git add model_prices_and_context_window.json 
+          git commit -m "Update model_prices_and_context_window.json file: $(date +'%Y-%m-%d')" 
+          gh pr create --title "Update model_prices_and_context_window.json file" \
+            --body "Automated update for model_prices_and_context_window.json" \
+            --head auto-update-price-and-context-window-$(date +'%Y-%m-%d') \
+            --base main
+        env:
+          GH_TOKEN: ${{ secrets.GH_TOKEN }}

.github/workflows/auto_update_price_and_context_window_file.py

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+import asyncio
+import aiohttp
+import json
+
+# Asynchronously fetch data from a given URL
+async def fetch_data(url):
+    try:
+        # Create an asynchronous session
+        async with aiohttp.ClientSession() as session:
+            # Send a GET request to the URL
+            async with session.get(url) as resp:
+                # Raise an error if the response status is not OK
+                resp.raise_for_status()
+                # Parse the response JSON
+                resp_json = await resp.json()
+                print("Fetch the data from URL.")
+                # Return the 'data' field from the JSON response
+                return resp_json['data']
+    except Exception as e:
+        # Print an error message if fetching data fails
+        print("Error fetching data from URL:", e)
+        return None
+
+# Synchronize local data with remote data
+def sync_local_data_with_remote(local_data, remote_data):
+    # Update existing keys in local_data with values from remote_data
+    for key in (set(local_data) & set(remote_data)):
+        local_data[key].update(remote_data[key])
+
+    # Add new keys from remote_data to local_data
+    for key in (set(remote_data) - set(local_data)):
+        local_data[key] = remote_data[key]
+
+# Write data to the json file
+def write_to_file(file_path, data):
+    try:
+        # Open the file in write mode
+        with open(file_path, "w") as file:
+            # Dump the data as JSON into the file
+            json.dump(data, file, indent=4)
+        print("Values updated successfully.")
+    except Exception as e:
+        # Print an error message if writing to file fails
+        print("Error updating JSON file:", e)
+
+# Update the existing models and add the missing models
+def transform_remote_data(data):
+    transformed = {}
+    for row in data:
+        # Add the fields 'max_tokens' and 'input_cost_per_token'
+        obj = {
+            "max_tokens": row["context_length"],
+            "input_cost_per_token": float(row["pricing"]["prompt"]),
+        }
+
+        # Add 'max_output_tokens' as a field if it is not None
+        if "top_provider" in row and "max_completion_tokens" in row["top_provider"] and row["top_provider"]["max_completion_tokens"] is not None:
+            obj['max_output_tokens'] = int(row["top_provider"]["max_completion_tokens"])
+
+        # Add the field 'output_cost_per_token'
+        obj.update({
+            "output_cost_per_token": float(row["pricing"]["completion"]),
+        })
+
+        # Add field 'input_cost_per_image' if it exists and is non-zero
+        if "pricing" in row and "image" in row["pricing"] and float(row["pricing"]["image"]) != 0.0:
+            obj['input_cost_per_image'] = float(row["pricing"]["image"])
+
+        # Add the fields 'litellm_provider' and 'mode'
+        obj.update({
+            "litellm_provider": "openrouter",
+            "mode": "chat"
+        })
+
+        # Add the 'supports_vision' field if the modality is 'multimodal'
+        if row.get('architecture', {}).get('modality') == 'multimodal':
+            obj['supports_vision'] = True
+
+        # Use a composite key to store the transformed object
+        transformed[f'openrouter/{row["id"]}'] = obj
+
+    return transformed
+
+
+# Load local data from a specified file
+def load_local_data(file_path):
+    try:
+        # Open the file in read mode
+        with open(file_path, "r") as file:
+            # Load and return the JSON data
+            return json.load(file)
+    except FileNotFoundError:
+        # Print an error message if the file is not found
+        print("File not found:", file_path)
+        return None
+    except json.JSONDecodeError as e:
+        # Print an error message if JSON decoding fails
+        print("Error decoding JSON:", e)
+        return None
+
+def main():
+    local_file_path = "model_prices_and_context_window.json"  # Path to the local data file
+    url = "https://openrouter.ai/api/v1/models"  # URL to fetch remote data
+
+    # Load local data from file
+    local_data = load_local_data(local_file_path)
+    # Fetch remote data asynchronously
+    remote_data = asyncio.run(fetch_data(url))
+    # Transform the fetched remote data
+    remote_data = transform_remote_data(remote_data)
+
+    # If both local and remote data are available, synchronize and save
+    if local_data and remote_data:
+        sync_local_data_with_remote(local_data, remote_data)
+        write_to_file(local_file_path, local_data)
+    else:
+        print("Failed to fetch model data from either local file or URL.")
+
+# Entry point of the script
+if __name__ == "__main__":
+    main()