Initial commit — Mek-Tech AI Consultancy Framework v2.0

2026-07-12 21:54:22 +00:00
commit 18921c021b
180 changed files with 28518 additions and 0 deletions
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+"""Pydantic v2 data models for AI-driven Lead Generation & Tech Scoping."""
+from __future__ import annotations
+from pydantic import BaseModel, Field
+from typing import List, Optional
+
+
+class CompanyTechProfile(BaseModel):
+    company_name: str = Field(
+        ...,
+        description="Official company name as detected from the page content",
+        min_length=1,
+    )
+    detected_technologies: List[str] = Field(
+        default_factory=list,
+        description="Detected technologies: Spark, Kafka, AWS, Kubernetes, Snowflake, Airflow, dbt, etc.",
+    )
+    current_pain_points: List[str] = Field(
+        default_factory=list,
+        description="Inferred pain points: legacy migration, data quality, scalability, missing AI/ML, etc.",
+    )
+    estimated_data_maturity: Optional[str] = Field(
+        default="Medium",
+        description="Estimated data maturity level: Low, Medium, or High",
+    )
+    outreach_hook: Optional[str] = Field(
+        default="",
+        description="Concrete reason why a Forward Deployed Engineer can help this company right now",
+    )
+    industry: Optional[str] = Field(
+        default=None,
+        description="Detected industry or sector",
+    )
+    company_size_hint: Optional[str] = Field(
+        default=None,
+        description="Estimated company size: Startup, Scale-up, Mid-market, Enterprise",
+    )
+    tech_blog_posts: Optional[str] = Field(
+        default=None,
+        description="URL to engineering/tech blog if detected",
+    )
+    hiring_roles: List[str] = Field(
+        default_factory=list,
+        description="Job titles/roles detected from careers page: Data Engineer, ML Engineer, DevOps, etc.",
+    )
+    desired_skills: List[str] = Field(
+        default_factory=list,
+        description="Specific skills/technologies they are hiring for: Python, Spark, Terraform, dbt, etc.",
+    )
+    job_listings_url: Optional[str] = Field(
+        default=None,
+        description="URL to careers/jobs page if detected on the site",
+    )
+    extracted_at: Optional[str] = Field(
+        default=None,
+        description="ISO timestamp of extraction",
+    )
+    source_url: Optional[str] = Field(
+        default=None,
+        description="Original URL that was scraped",
+    )
+
+
+class ScrapeResult(BaseModel):
+    url: str
+    title: str
+    text_content: str
+    text_length: int
+    status_code: Optional[int] = None
+    error: Optional[str] = None
+
+
+class LeadGenRequest(BaseModel):
+    url: str = Field(..., description="URL of the target company page to analyze")
+    force_refresh: bool = Field(default=False, description="Skip cache and force fresh scrape")
+
+
+class LeadGenResponse(BaseModel):
+    success: bool
+    profile: Optional[CompanyTechProfile] = None
+    error: Optional[str] = None
+    elapsed_ms: Optional[float] = None