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bug fixes for motia-content-creation #186

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6 changes: 5 additions & 1 deletion motia-content-creation/.gitignore
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Expand Up @@ -106,4 +106,8 @@ temp/
.Spotlight-V100
.Trashes
ehthumbs.db
Thumbs.db
Thumbs.db

# Typescript
types.d.ts
package-lock.json
1 change: 1 addition & 0 deletions motia-content-creation/README.md
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Expand Up @@ -46,6 +46,7 @@ API → Scrape → Generate → Schedule
2. **Install project dependencies:**
```bash
npm install or pnpm install
npx motia install
```

3. **Configure environment:**
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13 changes: 8 additions & 5 deletions motia-content-creation/package.json
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Expand Up @@ -18,17 +18,20 @@
"web-scraping"
],
"dependencies": {
"motia": "^0.4.0-beta.90",
"@mendable/firecrawl-js": "^1.0.0",
"openai": "^4.90.0",
"axios": "^1.10.0",
"dotenv": "^16.5.0",
"zod": "^3.25.67",
"axios": "^1.10.0"
"install": "^0.13.0",
"motia": "^0.4.0-beta.90",
"openai": "^4.90.0",
"or": "^0.2.0",
"pnpm": "^10.15.0",
"zod": "^3.25.67"
},
Comment on lines +22 to 30
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💡 Verification agent

🧩 Analysis chain

Prune likely-unused/supply-chain-risk dependencies from runtime deps.

Given the migration to Ollama in Python steps, these runtime deps look unnecessary in the Node package and can enlarge the attack surface:

  • openai (Node) — Python steps use ollama; no Node usage shown
  • pnpm — package manager should not be an app runtime dependency
  • install, or — uncommon packages; please justify usage
  • axios — only keep if the TS scheduling steps actually import it

Move truly-needed tools to devDependencies or remove entirely.

Run this script to confirm actual usage before removal:

If unused, apply this diff:

   "dependencies": {
     "@mendable/firecrawl-js": "^1.0.0",
-    "axios": "^1.10.0",
     "dotenv": "^16.5.0",
-    "install": "^0.13.0",
     "motia": "^0.4.0-beta.90",
-    "openai": "^4.90.0",
-    "or": "^0.2.0",
-    "pnpm": "^10.15.0",
     "zod": "^3.25.67"
   },

🏁 Script executed:

#!/bin/bash
# Verify usage of suspicious deps across the repo
set -euo pipefail
echo "Searching for imports/usages..."
rg -n -C2 -g '!**/node_modules/**' -g '!**/dist/**' -g '!**/build/**' \
  -e '\bfrom\s+["'\'']axios["'\'']' \
  -e '\brequire\(["'\'']axios["'\'']\)' \
  -e '\bfrom\s+["'\'']openai["'\'']' \
  -e '\brequire\(["'\'']openai["'\'']\)' \
  -e '\bfrom\s+["'\'']pnpm["'\'']' \
  -e '\brequire\(["'\'']pnpm["'\'']\)' \
  -e '\bfrom\s+["'\'']install["'\'']' \
  -e '\brequire\(["'\'']install["'\'']\)' \
  -e '\bfrom\s+["'\'']or["'\'']' \
  -e '\brequire\(["'\'']or["'\'']\)' \
  motia-content-creation

Length of output: 1385

Remove unused dependencies and retain only truly required runtime packages

The usage scan confirms:

  • axios is imported in
    • motia-content-creation/steps/schedule-twitter.step.ts (line 3)
    • motia-content-creation/steps/schedule-linkedin.step.ts (line 3)
      so it must remain in dependencies.
  • openai, pnpm, install, and or have no import/require occurrences and can be safely removed.

Apply this diff to motia-content-creation/package.json:

   "dependencies": {
     "@mendable/firecrawl-js": "^1.0.0",
     "axios": "^1.10.0",
     "dotenv": "^16.5.0",
     "motia": "^0.4.0-beta.90",
-    "openai": "^4.90.0",
-    "install": "^0.13.0",
-    "or": "^0.2.0",
-    "pnpm": "^10.15.0",
     "zod": "^3.25.67"
   },

This pruning reduces supply-chain risk without impacting any runtime code.

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
"axios": "^1.10.0",
"dotenv": "^16.5.0",
"zod": "^3.25.67",
"axios": "^1.10.0"
"install": "^0.13.0",
"motia": "^0.4.0-beta.90",
"openai": "^4.90.0",
"or": "^0.2.0",
"pnpm": "^10.15.0",
"zod": "^3.25.67"
},
"dependencies": {
"@mendable/firecrawl-js": "^1.0.0",
"axios": "^1.10.0",
"dotenv": "^16.5.0",
"motia": "^0.4.0-beta.90",
"zod": "^3.25.67"
},
🤖 Prompt for AI Agents 
In motia-content-creation/package.json around lines 22 to 30, the dependencies
list contains unused packages; keep "axios" (used in
steps/schedule-twitter.step.ts and steps/schedule-linkedin.step.ts) and remove
"openai", "pnpm", "install", and "or" from the dependencies section; update
package.json by deleting those four entries (and any trailing commas adjusted)
so only required runtime packages remain, then run a quick install (pnpm/npm)
and a codebase search to confirm no runtime imports were missed.

"devDependencies": {
"@types/node": "^20.17.28",
"@types/react": "^18.3.23",
"ts-node": "^10.9.2",
"typescript": "^5.8.3"
}
}
}
34 changes: 18 additions & 16 deletions motia-content-creation/steps/generate-linkedin.step.py
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Original file line number Diff line number Diff line change
@@ -1,15 +1,14 @@
import os
import json
import ollama
import asyncio
from pydantic import BaseModel, HttpUrl
from datetime import datetime
from dotenv import load_dotenv
from openai import AsyncOpenAI

load_dotenv()

OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')

openai_client = AsyncOpenAI(api_key=OPENAI_API_KEY)
OLLAMA_MODEL = os.getenv('OLLAMA_MODEL', 'deepseek-r1')

class GenerateInput(BaseModel):
requestId: str
Expand All @@ -35,21 +34,24 @@ async def handler(input, context):

linkedinPrompt = linkedinPromptTemplate.replace('{{title}}', input['title']).replace('{{content}}', input['content'])

context.logger.info("🔄 LinkedIn content generation started...")

linkedin_content = await openai_client.chat.completions.create(
model="gpt-4o",
messages=[{'role': 'user', 'content': linkedinPrompt}],
temperature=0.7,
max_tokens=2000,
response_format={'type': 'json_object'}
context.logger.info(f"🔄 LinkedIn content generation started using Ollama model: {OLLAMA_MODEL}...")
response = ollama.chat(
model=OLLAMA_MODEL,
messages=[{'role': 'user', 'content': linkedinPrompt}],
options={
'temperature': 0.7,
'num_predict': 2000
}
)


response_content = response['message']['content']
context.logger.info(f"Received raw response from Ollama: {response_content[:100]}...")

try:
linkedin_content = json.loads(linkedin_content.choices[0].message.content)
linkedin_content = json.loads(response['message']['content'])
except Exception:
linkedin_content = {'text': linkedin_content.choices[0].message.content}

linkedin_content = {'text': response['message']['content']}
context.logger.info(f"🎉 LinkedIn content generated successfully!")

await context.emit({
Expand Down
25 changes: 12 additions & 13 deletions motia-content-creation/steps/generate-twitter.step.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,13 +3,11 @@
from pydantic import BaseModel, HttpUrl
from datetime import datetime
from dotenv import load_dotenv
from openai import AsyncOpenAI
import ollama

load_dotenv()

OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')

openai_client = AsyncOpenAI(api_key=OPENAI_API_KEY)
OLLAMA_MODEL = os.getenv('OLLAMA_MODEL', 'deepseek-r1')

class GenerateInput(BaseModel):
requestId: str
Expand Down Expand Up @@ -37,18 +35,19 @@ async def handler(input, context):

context.logger.info("🔄 Twitter content generation started...")

twitter_content = await openai_client.chat.completions.create(
model="gpt-4o",
messages=[{'role': 'user', 'content': twitterPrompt}],
temperature=0.7,
max_tokens=2000,
response_format={'type': 'json_object'}
)
twitter_content = ollama.chat(
model=OLLAMA_MODEL,
messages=[{'role': 'user', 'content': twitterPrompt}],
options={
'temperature': 0.7,
'num_predict': 2000
}
)

try:
twitter_content = json.loads(twitter_content.choices[0].message.content)
twitter_content = json.loads(twitter_content['message']['content'])
except Exception:
twitter_content = {'text': twitter_content.choices[0].message.content}
twitter_content = {'text': twitter_content['message']['content']}

context.logger.info(f"🎉 Twitter content generated successfully!")

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14 changes: 7 additions & 7 deletions motia-content-creation/steps/scrape.step.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
import os
from pydantic import BaseModel, HttpUrl
from firecrawl import FirecrawlApp
from firecrawl import Firecrawl
from datetime import datetime
from dotenv import load_dotenv

Expand All @@ -26,15 +26,15 @@ class ScrapeInput(BaseModel):
async def handler(input, context):
context.logger.info(f"🕷️ Scraping article: {input['url']}")

app = FirecrawlApp(api_key=FIRECRAWL_API_KEY)
firecrawl = Firecrawl(api_key=FIRECRAWL_API_KEY)

scrapeResult = app.scrape_url(input['url'])
scrapeResult = firecrawl.scrape(input['url'], formats=["markdown"])
Comment on lines +29 to +31
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🛠️ Refactor suggestion

Guard missing FIRECRAWL_API_KEY and avoid blocking the event loop; also prefer a neutral client name

  • If FIRECRAWL_API_KEY is unset, Firecrawl(api_key=None) may fail later; fail fast with a clear message.
  • firecrawl.scrape(...) is synchronous; calling it in an async def may block the event loop during network I/O. Offload to a thread.
  • Minor: naming the variable firecrawl shadows the import symbol; client is clearer.

Apply:

-    firecrawl = Firecrawl(api_key=FIRECRAWL_API_KEY)
-
-    scrapeResult = firecrawl.scrape(input['url'], formats=["markdown"])
+    if not FIRECRAWL_API_KEY:
+        raise RuntimeError("FIRECRAWL_API_KEY is not set. Configure it in your environment.")
+
+    client = Firecrawl(api_key=FIRECRAWL_API_KEY)
+
+    # Offload sync HTTP call to a worker thread to avoid blocking the event loop
+    scrapeResult = await asyncio.to_thread(client.scrape, str(input['url']), formats=["markdown"])

Add outside this range:

import asyncio  # at the top with other imports
🤖 Prompt for AI Agents 
In motia-content-creation/steps/scrape.step.py around lines 29 to 31, guard
against a missing FIRECRAWL_API_KEY, avoid blocking the event loop, and rename
the variable: check that FIRECRAWL_API_KEY is set and raise a clear exception
immediately if not; instantiate the client into a variable named client (not
firecrawl) and call client.scrape off the event loop by wrapping the synchronous
call in asyncio.to_thread (or run_in_executor) from inside the async function;
also ensure import asyncio is added at the top with other imports.


if not scrapeResult.success:
raise Exception(f"Firecrawl scraping failed: {scrapeResult.error}")
if not hasattr(scrapeResult, 'markdown'):
raise Exception(f"Firecrawl scraping failed: No content returned")

content = scrapeResult.markdown
title = scrapeResult.metadata.get('title', 'Untitled Article')
content = scrapeResult.markdown or ''
title = getattr(scrapeResult.metadata, 'title', 'Untitled Article') if hasattr(scrapeResult, 'metadata') else 'Untitled Article'

context.logger.info(f"✅ Successfully scraped: {title} ({len(content) if content else 0} characters)")

Expand Down