Support provider-specific API key configuration

README.md

@@ -82,6 +82,8 @@ Repo2Readme/
     ├── pyproject.toml
     ├── repo2readme/
         ├── config.py
+        ├── llm/
+            ├── factory.py
         ├── cli/
             ├── main.py
         ├── loaders/

pyproject.toml

@@ -27,6 +27,8 @@ dependencies = [
     "langchain-community>=0.4.1",
     "langchain-groq>=1.1.1",
     "langchain-google-genai>=4.1.2",
+    "langchain-openai>=1.0.0",
+    "langchain-anthropic>=1.0.0",
 
     "groq>=0.37.1",
     "google-genai>=1.56.0"

repo2readme/cli/main.py

@@ -1,7 +1,11 @@
 import click
 from rich import print as rprint
 from rich.progress import Progress
-from repo2readme.config import get_api_keys, reset_api_keys
+from repo2readme.config import (
+    get_api_keys,
+    get_api_key,
+    reset_api_keys,
+)
 import os
 from repo2readme.utils.tree import generate_tree
 from repo2readme.utils.detect_language import detect_lang
@@ -48,7 +52,22 @@ def main():
     is_flag=True,
     help="Preview the analysis without making any API calls.",
 )
-def run(url, local, output, force, include_patterns, exclude_patterns, max_file_size_kb, dry_run):
+@click.option(
+    "--provider",
+    default=None,
+    help="LLM provider (groq, google, openai, anthropic, openrouter, ollama, etc.)",
+)
+@click.option(
+    "--model",
+    default=None,
+    help="LLM model name",
+)
+@click.option(
+    "--base-url",
+    default=None,
+    help="Base URL for OpenAI-compatible providers",
+)
+def run(url, local, output, force, include_patterns, exclude_patterns, max_file_size_kb, dry_run, provider, model, base_url,):
     """ Use --url for GitHub repo url and --local for local repo
     """
     if not url and not local:
@@ -121,9 +140,26 @@ def format_size(size_bytes):
                 return
 
         try:
-            groq_key, gemini_key = get_api_keys()
-            os.environ["GROQ_API_KEY"] = groq_key
-            os.environ["GOOGLE_API_KEY"] = gemini_key
+            if provider:
+                api_key = get_api_key(provider)
+
+                provider_env = {
+                    "groq": "GROQ_API_KEY",
+                    "google": "GOOGLE_API_KEY",
+                    "gemini": "GOOGLE_API_KEY",
+                    "openai": "OPENAI_API_KEY",
+                    "anthropic": "ANTHROPIC_API_KEY",
+                    "openrouter": "OPENROUTER_API_KEY",
+                    "together": "TOGETHER_API_KEY",
+            }
+
+                os.environ[provider_env[provider.lower()]] = api_key
+
+            else:
+                groq_key, gemini_key = get_api_keys()
+                os.environ["GROQ_API_KEY"] = groq_key
+                os.environ["GOOGLE_API_KEY"] = gemini_key
+
         except Exception as e:
             rprint(f"[red]Failed to configure API keys: {e}[/red]")
             return
@@ -143,11 +179,21 @@ def process_document(doc):
                 meta = doc["metadata"]
                 try:
                     lang = detect_lang(meta.get("file_type", "text"))
-                    summary = summarize_file(
-                        file_path=meta["file_path"],
-                        language=lang,
-                        content=doc["content"]
-                    )
+                    if provider or model or base_url:
+                        summary = summarize_file(
+                            file_path=meta["file_path"],
+                            language=lang,
+                            content=doc["content"],
+                            provider=provider,
+                            model_name=model,
+                            base_url=base_url,
+    )
+                    else:
+                        summary = summarize_file(
+                            file_path=meta["file_path"],
+                            language=lang,
+                            content=doc["content"],
+    )
                     with summaries_lock:
                         summaries.append(summary)
                 except Exception as e:
@@ -175,7 +221,10 @@ def process_document(doc):
             "max_iterations": 3,
             "latest_readme": "",
             'best_score': 0.0,
-            "best_readme": ""
+            "best_readme": "",
+            "provider": provider,
+            "model": model,
+            "base_url": base_url,
         }
 
         final_state = workflow.invoke(initial_state)

repo2readme/config.py

@@ -16,31 +16,54 @@ def save_env(data):
     with open(ENV_PATH, "w") as f:
         json.dump(data, f, indent=4)
 
-
 def get_api_keys():
     env = load_env()
 
     groq = env.get("GROQ_API_KEY")
     gemini = env.get("GOOGLE_API_KEY")
 
-    if groq and gemini:
-        return groq, gemini
-
-    rprint("[yellow]API keys are missing! Let's add them.[/yellow]\n")
-
     if not groq:
-        groq = input("Enter your Groq API key: ").strip()
+        groq = get_api_key("groq")
+
     if not gemini:
-        gemini = input("Enter your Google Gemini API key: ").strip()
+        gemini = get_api_key("google")
+
+    return groq, gemini
+
+def get_api_key(provider: str):
+    env = load_env()
 
-    env["GROQ_API_KEY"] = groq
-    env["GOOGLE_API_KEY"] = gemini
+    provider_map = {
+        "groq": "GROQ_API_KEY",
+        "google": "GOOGLE_API_KEY",
+        "gemini": "GOOGLE_API_KEY",
+        "openai": "OPENAI_API_KEY",
+        "anthropic": "ANTHROPIC_API_KEY",
+        "openrouter": "OPENROUTER_API_KEY",
+        "together": "TOGETHER_API_KEY",
+    }
 
+    provider = provider.lower()
+
+    if provider not in provider_map:
+        raise ValueError(f"Unsupported provider: {provider}")
+
+    env_var = provider_map[provider]
+    api_key = env.get(env_var)
+
+    if api_key:
+        return api_key
+
+    rprint(f"[yellow]{provider} API key is missing![/yellow]\n")
+
+    api_key = input(f"Enter your {provider} API key: ").strip()
+
+    env[env_var] = api_key
     save_env(env)
 
-    rprint("[green]API keys saved successfully![/green]")
+    rprint("[green]API key saved successfully![/green]")
 
-    return groq, gemini
+    return api_key
 
 
 def reset_api_keys():

repo2readme/llm/factory.py

@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+import os
+
+from langchain_core.language_models.chat_models import BaseChatModel
+
+def create_llm(
+    provider: str,
+    model: str,
+    api_key: str | None = None,
+    base_url: str | None = None,
+    **kwargs,
+) -> BaseChatModel:
+    """
+    Factory function to create a LangChain chat model.
+
+    Parameters
+    ----------
+    provider : str
+        LLM provider name.
+    model : str
+        Model name.
+    api_key : str | None
+        Optional API key. Falls back to environment variable.
+    base_url : str | None
+        Optional base URL for OpenAI-compatible APIs.
+    """
+
+    provider = provider.lower()
+
+    if provider == "groq":
+        from langchain_groq import ChatGroq
+        return ChatGroq(
+            model=model,
+            api_key=api_key or os.getenv("GROQ_API_KEY"),
+            **kwargs,
+        )
+
+    elif provider in ("google", "gemini"):
+        from langchain_google_genai import ChatGoogleGenerativeAI
+        return ChatGoogleGenerativeAI(
+            model=model,
+            google_api_key=api_key or os.getenv("GOOGLE_API_KEY"),
+            **kwargs,
+        )
+
+    elif provider == "openai":
+        from langchain_openai import ChatOpenAI
+        return ChatOpenAI(
+            model=model,
+            api_key=api_key or os.getenv("OPENAI_API_KEY"),
+            base_url=base_url,
+            **kwargs,
+        )
+
+    elif provider == "anthropic":
+        from langchain_anthropic import ChatAnthropic
+        return ChatAnthropic(
+            model=model,
+            api_key=api_key or os.getenv("ANTHROPIC_API_KEY"),
+            **kwargs,
+        )
+
+    elif provider == "openrouter":
+        from langchain_openai import ChatOpenAI
+        return ChatOpenAI(
+            model=model,
+            api_key=api_key or os.getenv("OPENROUTER_API_KEY"),
+            base_url=base_url or "https://openrouter.ai/api/v1",
+            **kwargs,
+        )
+
+    else:
+        raise ValueError(
+            f"Unsupported provider '{provider}'."
+        )

repo2readme/readme/agent_workflow.py

@@ -13,6 +13,9 @@ class ReadmeState(TypedDict):
     best_score:float
     iteration_no:int
     max_iterations:int
+    provider: str | None
+    model: str | None
+    base_url: str | None
 
 def generate_readme_node(state:ReadmeState):
     latest_readme = (
@@ -22,14 +25,17 @@ def generate_readme_node(state:ReadmeState):
        summaries=state['summaries'],
        tree_structure=state['tree_structure'],
        feedback=state['feedback'],
-       latest_readme=latest_readme
+       latest_readme=latest_readme,
+       provider=state["provider"],
+       model_name=state["model"],
+       base_url=state["base_url"]
     )
     return {
         'readme':[readme]
     }
 def readme_reviewer_node(state:ReadmeState):
     latest_readme=state['readme'][-1]
-    review=readme_reviewer(latest_readme)
+    review=readme_reviewer(latest_readme,provider=state["provider"], model_name=state["model"], base_url=state["base_url"])
     best_score=state['best_score']
     best_readme=state['best_readme']
     if review.score>best_score:

repo2readme/readme/readme_generator.py

@@ -1,14 +1,15 @@
-from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain_groq import ChatGroq
-import os
 from dotenv import load_dotenv
 load_dotenv()
 from langchain_core.prompts import PromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from typing import List
-def generate_readme(summaries:List[str],tree_structure:str,feedback:List[str],latest_readme:str):
-    api_key = os.getenv("GOOGLE_API_KEY")
-    model=ChatGoogleGenerativeAI(model="gemini-2.5-flash", google_api_key=api_key)
+from repo2readme.llm.factory import create_llm
+def generate_readme(summaries:List[str],tree_structure:str,feedback:List[str],latest_readme:str,provider:str, model_name:str, base_url:str):
+    model = create_llm(
+    provider= provider or "groq",
+    model= model_name or "openai/gpt-oss-120b",
+    base_url=base_url
+)
 
     prompt = PromptTemplate(
     template="""

repo2readme/readme/reviewer_agent.py

@@ -1,18 +1,26 @@
 from langchain_core.output_parsers import PydanticOutputParser
 from pydantic import BaseModel,Field
 from langchain_core.prompts import PromptTemplate
-from langchain_google_genai import ChatGoogleGenerativeAI
 import os
 from dotenv import load_dotenv
+from repo2readme.llm.factory import create_llm
 
 load_dotenv()
 class ReviewSchema(BaseModel):
     score:float=Field(description="A score between 1 and 10 based on the quality of the README")
     feedback:str=Field(description="Actionable comment how to improve the README")
 
-def readme_reviewer(readme:str):
-    api_key = os.getenv("GOOGLE_API_KEY")
-    model=ChatGoogleGenerativeAI(model="gemini-2.5-flash", google_api_key=api_key)
+def readme_reviewer(
+    readme: str,
+    provider: str | None = None,
+    model_name: str | None = None,
+    base_url: str | None = None,
+):
+    model = create_llm(
+    provider=provider or "google",
+    model=model_name or "gemini-2.5-flash",
+    base_url=base_url,
+)
     parser=PydanticOutputParser(pydantic_object=ReviewSchema)
     review_prompt=PromptTemplate(
         template="""

repo2readme/summarize/summary.py

@@ -1,17 +1,18 @@
-from langchain_groq import ChatGroq
 from langchain_core.prompts import PromptTemplate
 from dotenv import load_dotenv
 import os
 from langchain_core.output_parsers import JsonOutputParser
+from repo2readme.llm.factory import create_llm
 
 load_dotenv()
 
 
-def create_summarizer(file_path: str, language: str, content: str):
-    model = ChatGroq(
-        model="openai/gpt-oss-120b",
-        api_key=os.getenv("GROQ_API_KEY"),
-        temperature=0.2, 
+def create_summarizer(file_path, language,
+    content,provider=None, model_name=None, base_url=None,):
+    model = create_llm(
+        provider=provider or "groq",
+        model=model_name or "openai/gpt-oss-120b",
+        base_url=base_url, 
     )
     parser=JsonOutputParser()
     prompt = PromptTemplate(
@@ -80,9 +81,16 @@ def create_summarizer(file_path: str, language: str, content: str):
     return chain
 
 
-def summarize_file(file_path: str, language: str, content: str):
+def summarize_file(
+    file_path,
+    language,
+    content,
+    provider=None,
+    model_name=None,
+    base_url=None,
+):
     try:
-        chain = create_summarizer(file_path, language, content)
+        chain = create_summarizer(file_path, language, content, provider, model_name, base_url,)
         return chain.invoke({
             "file_path": file_path.replace("\\", "/"),
             "language": language,