Blog-to-Social Converter

export SENSO_API_KEY="YOUR_API_KEY"
export FIRECRAWL_KEY="YOUR_FIRECRAWL_KEY"
pip install requests firecrawl-py rich

import hashlib, os, sys, time, requests
from firecrawl import FirecrawlApp

SENSO_API_KEY = os.environ["SENSO_API_KEY"]
FIRECRAWL_KEY = os.environ["FIRECRAWL_KEY"]
BASE = "https://apiv2.senso.ai/api/v1"
HEADERS = {"X-API-Key": SENSO_API_KEY, "Content-Type": "application/json"}

blog_url = sys.argv[1] if len(sys.argv) > 1 else "https://your-blog.com/great-article"

# ── 1. Scrape the blog post ──────────────────────────────────

print(f"Scraping {blog_url}...")
fc = FirecrawlApp(api_key=FIRECRAWL_KEY)
page = fc.scrape_url(blog_url, params={"formats": ["markdown"]})
markdown = page.get("markdown", "")
title = page.get("metadata", {}).get("title", "Blog Post")
print(f"Got: {title} ({len(markdown)} chars)")

# ── 2. Ingest into Senso ─────────────────────────────────────

file_bytes = markdown.encode("utf-8")
filename = f"{title[:50].replace(' ', '-').lower()}.md"

resp = requests.post(f"{BASE}/org/kb/upload", headers=HEADERS, json={
    "files": [{
        "filename": filename,
        "file_size_bytes": len(file_bytes),
        "content_type": "text/markdown",
        "content_hash_md5": hashlib.md5(file_bytes).hexdigest(),
    }]
})
result = resp.json()["results"][0]
content_id = result["content_id"]

# Upload to S3. Set Content-Type to the SAME value declared above —
# the presigned URL signs it, so a mismatch is rejected by S3.
requests.put(result["upload_url"], data=file_bytes,
             headers={"Content-Type": "text/markdown"})
print(f"Uploaded -> {content_id}")

# /org/kb/upload returns a CONTENT id, but the /org/kb/nodes/{id}/... endpoints
# need the NODE id — resolve it by matching the content id in the KB tree.
nodes = requests.get(f"{BASE}/org/kb/find", headers=HEADERS,
                     params={"q": filename}).json()["nodes"]
node_id = next(n["kb_node_id"] for n in nodes if n["content_id"] == content_id)

# Poll the KB node until ingestion finishes. (GET /org/content/{id} is for
# generated content; KB sources are read via /org/kb/nodes/{id}/content.)
while True:
    node = requests.get(f"{BASE}/org/kb/nodes/{node_id}/content", headers=HEADERS).json()
    if node.get("processing_status") == "complete":
        break
    time.sleep(1)
print("Processing complete.")

# ── 3. Set up brand kit ──────────────────────────────────────

# The brand kit defines your org's voice and writing rules.
# `guidelines` accepts only the keys below — any other key is
# rejected with a 400. The content engine uses them during generation.

requests.put(f"{BASE}/org/brand-kit", headers=HEADERS, json={
    "guidelines": {
        "brand_name": "Acme Corp",
        "brand_domain": "acme.com",
        "brand_description": "Developer tools for API infrastructure",
        "voice_and_tone": "Clear, direct, technically confident. Avoid jargon when a simpler word works.",
        "author_persona": "A senior engineer who has shipped at scale",
        "global_writing_rules": [
            "Use active voice",
            "Lead with the insight, not the setup",
            "No em-dashes or semicolons",
        ],
    }
})
print("Brand kit saved.")

# ── 4. Create content types ──────────────────────────────────

# Content types are reusable output templates. `config` accepts only
# these keys (any other key is rejected with a 400): `template`,
# `template_spec`, `cta_text`, `cta_destination`, and `writing_rules`.

content_types = [
    {
        "name": "Tweet Thread",
        "config": {
            "template": "A thread of 3-5 tweets. First tweet hooks the reader. Last tweet has the CTA. Each tweet ≤280 chars.",
            "cta_text": "Read the full post",
            "cta_destination": blog_url,
            "writing_rules": [
                "One idea per tweet",
                "Use line breaks for readability",
                "No hashtags in the thread body",
            ],
        },
    },
    {
        "name": "LinkedIn Post",
        "config": {
            "template": "A single LinkedIn post under 1300 characters. Open with a bold statement. End with a question to drive comments.",
            "cta_text": "Link in comments",
            "cta_destination": blog_url,
            "writing_rules": [
                "Professional but not stiff",
                "Use short paragraphs (1-2 sentences)",
                "Include one concrete metric or example",
            ],
        },
    },
]

type_ids = {}
for ct in content_types:
    resp = requests.post(f"{BASE}/org/content-types", headers=HEADERS, json=ct)
    if resp.status_code == 201:
        data = resp.json()
        type_ids[ct["name"]] = data["content_type_id"]
        print(f"Created content type: {ct['name']} -> {data['content_type_id']}")
    elif resp.status_code == 409:
        # Already exists — list and find it
        existing = requests.get(f"{BASE}/org/content-types", headers=HEADERS).json()
        for t in existing.get("content_types", []):
            if t["name"] == ct["name"]:
                type_ids[ct["name"]] = t["content_type_id"]
                print(f"Content type exists: {ct['name']} -> {t['content_type_id']}")
                break

# ── 5. Create a prompt ────────────────────────────────────────

# A prompt is the question that drives generation.
# Types: awareness, consideration, decision, evaluation

resp = requests.post(f"{BASE}/org/prompts", headers=HEADERS, json={
    "question_text": f"What are the key takeaways from: {title}?",
    "type": "awareness",
})
prompt = resp.json()
prompt_id = prompt["prompt_id"]
print(f"Created prompt: {prompt_id}")

# ── 6. Generate content for each type ─────────────────────────

for name, type_id in type_ids.items():
    print(f"\nGenerating {name}...")

    resp = requests.post(
        f"{BASE}/org/content-generation/sample",
        headers=HEADERS,
        json={
            "geo_question_id": prompt_id,
            "content_type_id": type_id,
        },
    )

    if resp.status_code == 202:
        job = resp.json()
        while True:
            status = requests.get(
                f"{BASE}/org/content-generation/sample-jobs/{job['sample_job_id']}",
                headers=HEADERS,
            ).json()
            if status["status"] in {"completed", "failed", "expired"}:
                break
            time.sleep(2)

        if status["status"] != "completed":
            print(f"  Error: {status.get('error', {}).get('message', status['status'])}")
            continue

        gen = status["result"]
        print(f"  Content ID:  {gen['content_id']}")
        print(f"  SEO Title:   {gen['seo_title']}")
        print(f"  URL Slug:    {gen['url_slug']}")
        print(f"  Status:      {gen['editorial_status']}")
        print(f"  ---")
        # Print first 300 chars of the generated markdown
        print(f"  {gen['raw_markdown'][:300]}...")
    else:
        print(f"  Error {resp.status_code}: {resp.text}")

python blog_to_social.py https://your-blog.com/great-article

Scraping https://your-blog.com/great-article...
Got: 10 Lessons from Scaling Our API (3842 chars)
Uploaded -> a1b2c3d4-...
Processing complete.
Brand kit saved.
Created content type: Tweet Thread -> e5f6a7b8-...
Created content type: LinkedIn Post -> c9d0e1f2-...
Created prompt: d3e4f5a6-...

Generating Tweet Thread...
  Content ID:  f7a8b9c0-...
  SEO Title:   10 Lessons from Scaling Our API - Thread
  URL Slug:    10-lessons-scaling-api-thread
  Status:      draft
  ---
  1/ We scaled our API from 100 to 10,000 requests/sec last year.
  Here are 10 hard-won lessons...

Generating LinkedIn Post...
  Content ID:  a0b1c2d3-...
  SEO Title:   What We Learned Scaling to 10K RPS
  URL Slug:    learned-scaling-10k-rps
  Status:      draft
  ---
  After a year of scaling our API infrastructure, here are the
  insights that actually mattered...

PUT /org/brand-kit
{
  "guidelines": {
    "brand_name": "Acme Corp",
    "brand_domain": "acme.com",
    "brand_description": "Developer tools for API infrastructure",
    "voice_and_tone": "Clear, direct, technically confident.",
    "author_persona": "A senior engineer who has shipped at scale",
    "global_writing_rules": ["Use active voice", "Lead with the insight"]
  }
}

POST /org/content-types
{
  "name": "Tweet Thread",
  "config": {
    "template": "A thread of 3-5 tweets...",
    "cta_text": "Read the full post",
    "cta_destination": "https://your-blog.com/article",
    "writing_rules": ["One idea per tweet"]
  }
}

POST /org/prompts
{
  "question_text": "What are the key takeaways?",
  "type": "awareness"
}

POST /org/content-generation/sample
{
  "geo_question_id": "uuid",
  "content_type_id": "uuid"
}