Blue hawk demo

.github/workflows/check_code_snippets.yml

@@ -0,0 +1,39 @@
+name: Test W&B Doc Code Snippets
+on: [pull_request]
+
+jobs:
+  generate-matrix:
+    runs-on: ubuntu-latest
+    outputs:
+      scripts: ${{ steps.list-scripts.outputs.scripts }}
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Find Python scripts
+        id: list-scripts
+        run: |
+           SCRIPTS=$(find code_examples/source -name "*.py" | jq -R -s -c 'split("\n")[:-1]')
+           echo "scripts=$SCRIPTS" >> $GITHUB_ENV
+           echo "::set-output name=scripts::$SCRIPTS"
+
+  test:
+    needs: generate-matrix
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        script: ${{ fromJson(needs.generate-matrix.outputs.scripts) }}
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: "3.10"
+
+      - name: Install and check dependencies
+        run: bash code_examples/check_dependencies.sh
+
+      - name: Run W&B script
+        run: python3 ${{ matrix.script }}

.github/workflows/gpt-editor-ci-version.yml

@@ -249,6 +249,9 @@ jobs:
               # Find changed sections using sequence matcher
               matcher = difflib.SequenceMatcher(None, original_lines, improved_lines)
 
+              # Get sections that have changes
+              sections_to_process = []
+
               for tag, i1, i2, j1, j2 in matcher.get_opcodes():
                   # Only process changes (not matches)
                   if tag in ('replace', 'delete', 'insert'):
@@ -262,13 +265,29 @@ jobs:
                       line_end = i2  # i2 is exclusive in Python, but we need inclusive for line ranges
 
                       # Only create suggestions for sections that overlap with PR changes if filtering
-                      if not filter_by_changes or (modified_line_ranges and any(
+                      should_process = not filter_by_changes or (modified_line_ranges and any(
                           max(range_start, line_start) <= min(range_end, line_end)
                           for range_start, range_end in modified_line_ranges
-                      )):
-                          create_suggestion(file_path, line_start, line_end, original_section, improved_section)
+                      ))
+
+                      if should_process:
+                          # Store the section for processing
+                          sections_to_process.append((line_start, line_end, original_section, improved_section))
                       else:
                           print(f"Skipping suggestion for {file_path} lines {line_start}-{line_end} as they weren't modified in the PR")
+
+              # Process accumulated sections with proper line information
+              # Sort by starting line to process in order
+              for line_start, line_end, original_section, improved_section in sorted(sections_to_process, key=lambda x: x[0]):
+                  if len(original_section) == 0 and len(improved_section) == 0:
+                      continue  # Skip if both sections are empty
+
+                  # Check for empty original section (insertion case)
+                  if len(original_section) == 0:
+                      # Insertion - point to the line where we want to insert
+                      create_suggestion(file_path, line_start, line_start, original_section, improved_section)
+                  else:
+                      create_suggestion(file_path, line_start, line_end, original_section, improved_section)
 
           def create_suggestion(file_path, start_line, end_line, original_section, improved_section):
               """Create a GitHub PR review comment with a suggestion"""
@@ -277,12 +296,22 @@ jobs:
               repo = os.environ.get('GITHUB_REPOSITORY')
               action_url = f"https://github.com/{repo}/actions/runs/{run_id}"
 
+              # Validate that the line numbers make sense
+              if start_line < 1:
+                  print(f"Warning: Invalid start line {start_line}, adjusting to 1")
+                  start_line = 1
+
               # Format the suggestion with link to the action run
               body = f"```suggestion\n{chr(10).join(improved_section)}\n```\n\n*[Generated by GPT Editor]({action_url})*"
 
               pr_number = os.environ.get('PR_NUMBER')
               github_token = os.environ.get('GITHUB_TOKEN')
 
+              # Debug output to help track line mappings
+              print(f"Suggesting change for {file_path} lines {start_line}-{end_line}")
+              print(f"Original ({len(original_section)} lines): {original_section[:1]}...")
+              print(f"Improved ({len(improved_section)} lines): {improved_section[:1]}...")
+
               # Create a review comment using GitHub API
               try:
                   # First get the latest commit SHA on the PR
@@ -374,4 +403,4 @@ jobs:
             -H "Authorization: token $GITHUB_TOKEN" \
             -H "Accept: application/vnd.github.v3+json" \
             https://api.github.com/repos/$GITHUB_REPOSITORY/issues/$PR_NUMBER/comments \
-            -d "$COMMENT_BODY"
+            -d "$COMMENT_BODY"

code_examples/check_dependencies.sh

@@ -0,0 +1,5 @@
+#!/bin/bash
+REQUIREMENTS_PATH="code_examples/requirements.txt"
+pip install -r "$REQUIREMENTS_PATH" && echo "All packages installed successfully!" || echo "Installation failed."
+
+python -c "import pkgutil; import sys; packages = [pkg.strip() for pkg in open('$REQUIREMENTS_PATH')]; missing = [p for p in packages if not pkgutil.find_loader(p)]; sys.exit(1) if missing else print('✅ All packages are installed.')"

code_examples/requirements.txt

@@ -0,0 +1 @@
+wandb

code_examples/snippets/quickstart.snippet.all.py

@@ -0,0 +1,26 @@
+import wandb
+import random
+
+wandb.login()
+
+epochs = 10
+lr = 0.01
+
+run = wandb.init(
+    project="my-awesome-project",    # Specify your project
+    config={                         # Track hyperparameters and metadata
+        "learning_rate": lr,
+        "epochs": epochs,
+    },
+)
+
+offset = random.random() / 5
+print(f"lr: {lr}")
+
+# Simulate a training run
+for epoch in range(2, epochs):
+    acc = 1 - 2**-epoch - random.random() / epoch - offset
+    loss = 2**-epoch + random.random() / epoch + offset
+    print(f"epoch={epoch}, accuracy={acc}, loss={loss}")
+    wandb.log({"accuracy": acc, "loss": loss})
+run.finish()

code_examples/snippets/quickstart.snippet.import.py

@@ -0,0 +1,2 @@
+import wandb
+import random

code_examples/snippets/quickstart.snippet.init.py

@@ -0,0 +1,7 @@
+run = wandb.init(
+    project="my-awesome-project",    # Specify your project
+    config={                         # Track hyperparameters and metadata
+        "learning_rate": lr,
+        "epochs": epochs,
+    },
+)

code_examples/snippets/quickstart.snippet.login.py

@@ -0,0 +1 @@
+wandb.login()

code_examples/source/quickstart.py

@@ -0,0 +1,41 @@
+#!/usr/bin/env python3
+
+try:
+    # :snippet-start: all
+    # :snippet-start: import
+    import wandb
+    import random
+    # :snippet-end: import
+
+    # :snippet-start: login
+    wandb.login()
+    # :snippet-end: login
+
+    epochs = 10
+    lr = 0.01
+
+    # :snippet-start: init
+    run = wandb.init(
+        project="my-awesome-project",    # Specify your project
+        config={                         # Track hyperparameters and metadata
+            "learning_rate": lr,
+            "epochs": epochs,
+        },
+    )
+    # :snippet-end: init
+
+    offset = random.random() / 5
+    print(f"lr: {lr}")
+
+    # Simulate a training run
+    for epoch in range(2, epochs):
+        acc = 1 - 2**-epoch - random.random() / epoch - offset
+        loss = 2**-epoch + random.random() / epoch + offset
+        print(f"epoch={epoch}, accuracy={acc}, loss={loss}")
+        wandb.log({"accuracy": acc, "loss": loss})
+    run.finish()
+    # :snippet-end: all
+    exit(0)
+except Exception as e:
+    print(f"Error: {e}")
+    exit(1)

content/guides/quickstart.md

@@ -38,13 +38,18 @@ Install the `wandb` library and log in by following these steps:
 
 {{% tab header="Python" value="python" %}}
 
+Navigate to your terminal and run the following command:
 ```bash
 pip install wandb
 ```
-```python
-import wandb
-wandb.login()
-```
+
+Within your Python script, import the `wandb` library:
+
+{{< code language="python" source="/code_examples/snippets/quickstart.snippet.import.py" >}}
+
+Next, log in to W&B using the `wandb.login()` method:
+
+{{< code language="python" source="/code_examples/snippets/quickstart.snippet.login.py" >}}
 
 {{% /tab %}}
 
@@ -63,52 +68,15 @@ wandb.login()
 
 In your Python script or notebook, initialize a W&B run object with [`wandb.init()`]({{< relref "/ref/python/run.md" >}}). Use a dictionary for the `config` parameter to specify hyperparameter names and values:
 
-```python
-run = wandb.init(
-    project="my-awesome-project",  # Specify your project
-    config={                        # Track hyperparameters and metadata
-        "learning_rate": 0.01,
-        "epochs": 10,
-    },
-)
-```
+{{< code language="python" source="/code_examples/snippets/quickstart.snippet.init.py" >}}
 
 A [run]({{< relref "/guides/models/track/runs/" >}}) serves as the core element of W&B, used to [track metrics]({{< relref "/guides/models/track/" >}}), [create logs]({{< relref "/guides/core/artifacts/" >}}), and more.
 
 ## Assemble the components
 
 This mock training script logs simulated accuracy and loss metrics to W&B:
 
-```python
-# train.py
-import wandb
-import random
-
-wandb.login()
-
-epochs = 10
-lr = 0.01
-
-run = wandb.init(
-    project="my-awesome-project",    # Specify your project
-    config={                         # Track hyperparameters and metadata
-        "learning_rate": lr,
-        "epochs": epochs,
-    },
-)
-
-offset = random.random() / 5
-print(f"lr: {lr}")
-
-# Simulate a training run
-for epoch in range(2, epochs):
-    acc = 1 - 2**-epoch - random.random() / epoch - offset
-    loss = 2**-epoch + random.random() / epoch + offset
-    print(f"epoch={epoch}, accuracy={acc}, loss={loss}")
-    wandb.log({"accuracy": acc, "loss": loss})
-
-# run.log_code()
-```
+{{< code language="python" source="/code_examples/snippets/quickstart.snippet.all.py" >}}
 
 Visit the W&B App at [wandb.ai/home](https://wandb.ai/home) to view recorded metrics such as accuracy and loss during each training step.
 

layouts/shortcodes/code.html

@@ -0,0 +1,7 @@
+{{ $language := .Get "language" }}
+{{ $source := .Get "source" }}
+{{ $options := .Get "options" }}
+
+{{ with $source | readFile }}
+  {{ highlight (trim . "\n\r") $language $options }}
+{{ end }}