diff --git a/.gitignore b/.gitignore
index 79fec8ea..7adfae26 100644
--- a/.gitignore
+++ b/.gitignore
@@ -178,10 +178,9 @@ llm_cache/
 
 # Evaluation output folder
 eval_output*/
-lsc_eval/eval_output*/
 
 # DeepEval telemetry and configuration
-lsc_eval/.deepeval/
+.deepeval/
 
 # Keeping experimental changes here
-wip*/
\ No newline at end of file
+wip*/
diff --git a/README.md b/README.md
index 18573c21..7dc6408c 100644
--- a/README.md
+++ b/README.md
@@ -1,100 +1,152 @@
-# Lightspeed Core Evaluation
-Evaluation tooling for lightspeed-core project
+# LightSpeed Evaluation Framework
 
-## Installation
-- **Requires Python 3.11**
-- Install `uv`
-- Check `uv --version` is working
-- If running Python 3.11 from `venv`, make sure no conflicting packages are installed. In case of problems create a clean venv for Python 3.11 and `uv`.
-- Run `uv sync`
-- Optional: For development, run `make install-tools`
-    + if `uv` is not installed this will install `uv` by running `pip install uv` in your current Python environment.
+A comprehensive framework for evaluating GenAI applications.
 
+## 🎯 Key Features
 
-## Description
-Currently we have 2 types of evaluations.
-1. `consistency`: Ability to compare responses against ground-truth answer for specific provider+model. Objective of this evaluation is to flag any variation in specific provider+model response. Currently a combination of similarity distances are used to calculate final score. Cut-off scores are used to flag any deviations. This also stores a .csv file with query, pre-defined answer, API response & score. Input for this is a [json file](eval_data/question_answer_pair.json)
+- **Multi-Framework Support**: Seamlessly use metrics from Ragas, DeepEval, and custom implementations
+- **Turn & Conversation-Level Evaluation**: Support for both individual queries and multi-turn conversations  
+- **LLM Provider Flexibility**: OpenAI, Anthropic, Watsonx, Azure, Gemini, Ollama via LiteLLM
+- **Flexible Configuration**: Configurable environment & metric metadata
+- **Rich Output**: CSV, JSON, TXT reports + visualization graphs (pass rates, distributions, heatmaps)
+- **Early Validation**: Catch configuration errors before expensive LLM calls
+- **Statistical Analysis**: Statistics for every metric with score distribution analysis
+- **Agent Evaluation**: Framework for evaluating AI agent performance (future integration planned)
 
-2. `model`: Ability to compare responses against single ground-truth answer. Here we can do evaluation for more than one provider+model at a time. This creates a json file as summary report with scores (f1-score) for each provider+model. Along with selected QnAs from above json file, we can also provide additional QnAs using a parquet file (optional). [Sample QnA set (parquet)](eval_data/interview_qna_30_per_title.parquet) with 30 queries per OCP documentation title.
+## 🚀 Quick Start
 
-    ![Evaluation Metric & flow](assets/response_eval_flow.png)
+### Installation
 
-**Notes**
-- QnAs should `not` be used for model training or tuning. This is created only for evaluation purpose.
-- QnAs were generated from OCP docs by LLMs. It is possible that some of the questions/answers are not entirely correct. We are constantly trying to verify both Questions & Answers manually. If you find any QnA pair to be modified or removed, please create a PR.
-- OLS API should be ready/live with all the required provider+model configured.
-- It is possible that we want to run both consistency and model evaluation together. To avoid multiple API calls for same query, *model* evaluation first checks .csv file generated by *consistency* evaluation. If response is not present in csv file, then only we call API to get the response.
+```bash
+# From Git
+pip install git+https://github.com/lightspeed-core/lightspeed-evaluation.git
 
-### e2e test case
-
-These evaluations are also part of **e2e test cases**. Currently *consistency* evaluation is parimarily used to gate PRs. Final e2e suite will also invoke *model* evaluation which will use .csv files generated by earlier suites, if any file is not present then last suite will fail.
-
-### Usage
-```
-uv run evaluate
+# Local Development
+pip install uv
+uv sync
 ```
 
-### Input Data/QnA pool
-[Json file](eval_data/question_answer_pair.json)
-
-[Sample QnA set (parquet)](eval_data/interview_qna_30_per_title.parquet)
-
-Please refer above files for the structure, add new data accordingly.
-
-### Arguments
-**eval_type**: This will control which evaluation, we want to do. Currently we have 3 options.
-1. `consistency` -> Compares model specific answer for QnAs provided in json file
-2. `model` -> Compares set of models based on their response and generates a summary report. For this we can provide additional QnAs in parquet format, along with json file.
-3. `all` -> Both of the above evaluations.
-
-**eval_api_url**: OLS API url. Default is `http://localhost:8080`. If deployed in a cluster, then pass cluster API url.
-
-**eval_api_token_file**: Path to a text file containing OLS API token. Required, if OLS is deployed in cluster.
-
-**eval_scenario**: This is primarily required to indetify which pre-defined answers need to be compared. Values can be `with_rag`, `without_rag`. Currently we always do evaluation for the API with rag.
-
-**eval_query_ids**: Option to give set of query ids for evaluation. By default all queries are processed.
-
-**eval_provider_model_id**: We can provide set of provider/model combinations as ids for comparison.
-
-**qna_pool_file**: Applicable only for `model` evaluation. Provide file path to the parquet file having additional QnAs. Default is None.
-
-**eval_out_dir**: Directory, where output csv/json files will be saved.
-
-**eval_metrics**: By default all scores/metrics are calculated, but this decides which scores will be used to create the graph.
-This is a list of metrics. Ex: cosine, euclidean distance, precision/recall/F1 score, answer relevancy score, LLM based similarity score.
-
-**judge_provider / judge_model**: Provider / Model for judge LLM. This is required for LLM based evaluation (answer relevancy score, LLM based similarity score). This needs to be configured correctly through config yaml file. [Sample provider/model configuration](../../examples/olsconfig.yaml)
-
-**eval_modes**: Apart from OLS api, we may want to evaluate vanilla model or with just OLS paramaters/prompt/RAG so that we can have baseline score. This is a list of modes. Ex: vanilla, ols_param, ols_prompt, ols_rag, & ols (actual api).
+### Basic Usage
+
+```bash
+# Set API key
+export OPENAI_API_KEY="your-key"
+
+# Run evaluation
+lightspeed-eval --system-config config/system.yaml --eval-data config/evaluation_data.yaml
+
+## 📊 Supported Metrics
+
+### Turn-Level (Single Query)
+- **Ragas**
+  - Response Evaluation
+    - `faithfulness`
+    - `response_relevancy`
+  - Context Evaluation
+    - `context_recall`
+    - `context_relevance`
+    - `context_precision_without_reference`
+    - `context_precision_with_reference`
+- **Custom**
+  - Response Evaluation
+    - `answer_correctness`
+
+### Conversation-Level (Multi-turn)
+- **DeepEval**
+  - `conversation_completeness`
+  - `conversation_relevancy`
+  - `knowledge_retention`
+
+## ⚙️ Configuration
+
+### System Config (`config/system.yaml`)
+```yaml
+llm:
+  provider: "openai"
+  model: "gpt-4o-mini"
+  temperature: 0.0
+  timeout: 120
+
+metrics_metadata:
+  turn_level:
+    "ragas:faithfulness":
+      threshold: 0.8
+      type: "turn"
+      framework: "ragas"
+  
+  conversation_level:
+    "deepeval:conversation_completeness":
+      threshold: 0.8
+      type: "conversation"
+      framework: "deepeval"
+```
 
-### Outputs
-Evaluation scripts creates below files.
-- CSV file with response for given provider/model & modes.
-- response evaluation result with scores (for consistency check).
-- Final csv file with all results, json score summary & graph (for model evaluation)
+### Evaluation Data (`config/evaluation_data.yaml`)
+```yaml
+- conversation_group_id: "test_conversation"
+  description: "Sample evaluation"
+  
+  # Turn-level metrics (empty list = skip turn evaluation)
+  turn_metrics:
+    - "ragas:faithfulness"
+    - "custom:answer_correctness"
+  
+  # Turn-level metrics metadata (threshold + other properties)
+  turn_metrics_metadata:
+    "ragas:response_relevancy": 
+      threshold: 0.8
+      weight: 1.0
+    "custom:answer_correctness": 
+      threshold: 0.75
+  
+  # Conversation-level metrics (empty list = skip conversation evaluation)   
+  conversation_metrics:
+    - "deepeval:conversation_completeness"
+  
+  turns:
+    - turn_id: 1
+      query: "What is OpenShift?"
+      response: "Red Hat OpenShift powers the entire application lifecycle...."
+      contexts:
+        - content: "Red Hat OpenShift powers...."
+      expected_response: "Red Hat OpenShift...."
+```
 
-[Evaluation Result](eval_data/result/README.md)
+## 📈 Output & Visualization
+
+### Generated Reports
+- **CSV**: Detailed results with status, scores, reasons
+- **JSON**: Summary statistics with score distributions
+- **TXT**: Human-readable summary
+- **PNG**: 4 visualization types (pass rates, score distributions, heatmaps, status breakdown)
+
+### Key Metrics in Output
+- **PASS/FAIL/ERROR**: Status based on thresholds
+- **Actual Reasons**: DeepEval provides LLM-generated explanations, Custom metrics provide detailed reasoning
+- **Score Statistics**: Mean, median, standard deviation, min/max for every metric
+
+## 🧪 Development
+
+### Development Tools
+```bash
+uv sync --group dev
+uv run black .
+uv run ruff check .
+uv run mypy .
+uv run pyright .
+uv run pylint .
+uv run pytest tests --cov=src
+```
 
 ## Agent Evaluation
 For a detailed walkthrough of the new agent-evaluation framework, refer
 [lsc_agent_eval/README.md](lsc_agent_eval/README.md)
 
-## RAG retrieval script
-```
-python -m scripts.evaluation.query_rag
-```
-This is used to generate a .csv file having retrieved chunks for given set of queries with similarity score. This is not part of actual evaluation. But useful to do a spot check to understand the text that we send to LLMs as context (this may explain any deviation in the response)
-
-#### Arguments
-*db-path*: Path to the RAG index
-
-*product-index*: RAG index ID
-
-*model-path*: Path or name of the embedding model
+## Generate answers (optional - for creating test data)
+For generating answers (optional) refer [README-generate-answers](README-generate-answers.md)
 
-*queries*: Set of queries separated by space. If not passed default queries are used.
+## 📄 License & Contributing
 
-*top-k*: How many chunks we want to retrieve. Default is 10.
+This project is licensed under the Apache License 2.0. See the LICENSE file for details.
 
-*output_dir*: To save the .csv file.
\ No newline at end of file
+Contributions welcome - see development setup above for code quality tools.
\ No newline at end of file
diff --git a/archive/README.md b/archive/README.md
new file mode 100644
index 00000000..9a6561f3
--- /dev/null
+++ b/archive/README.md
@@ -0,0 +1,99 @@
+# Lightspeed Core Evaluation
+Evaluation tooling for lightspeed-core project. [Refer latest README.md](../README.md).
+
+**This is not maintained anymore.**
+
+## Installation
+- **Requires Python 3.11**
+- Install `pdm`
+- Check `pdm --version` is working
+- If running Python 3.11 from `venv`, make sure no conflicting packages are installed. In case of problems create a clean venv for Python 3.11 and `pdm`.
+- Run `pdm install`
+- Optional: For development, run `make install-tools`
+    + if `pdm` is not installed this will install `pdm` by running `pip install pdm` in your current Python environment.
+
+
+## Description
+Currently we have 2 types of evaluations.
+1. `consistency`: Ability to compare responses against ground-truth answer for specific provider+model. Objective of this evaluation is to flag any variation in specific provider+model response. Currently a combination of similarity distances are used to calculate final score. Cut-off scores are used to flag any deviations. This also stores a .csv file with query, pre-defined answer, API response & score. Input for this is a [json file](../eval_data/question_answer_pair.json)
+
+2. `model`: Ability to compare responses against single ground-truth answer. Here we can do evaluation for more than one provider+model at a time. This creates a json file as summary report with scores (f1-score) for each provider+model. Along with selected QnAs from above json file, we can also provide additional QnAs using a parquet file (optional). [Sample QnA set (parquet)](../eval_data/interview_qna_30_per_title.parquet) with 30 queries per OCP documentation title.
+
+    ![Evaluation Metric & flow](assets/response_eval_flow.png)
+
+**Notes**
+- QnAs should `not` be used for model training or tuning. This is created only for evaluation purpose.
+- QnAs were generated from OCP docs by LLMs. It is possible that some of the questions/answers are not entirely correct. We are constantly trying to verify both Questions & Answers manually. If you find any QnA pair to be modified or removed, please create a PR.
+- OLS API should be ready/live with all the required provider+model configured.
+- It is possible that we want to run both consistency and model evaluation together. To avoid multiple API calls for same query, *model* evaluation first checks .csv file generated by *consistency* evaluation. If response is not present in csv file, then only we call API to get the response.
+
+### e2e test case
+
+These evaluations are also part of **e2e test cases**. Currently *consistency* evaluation is parimarily used to gate PRs. Final e2e suite will also invoke *model* evaluation which will use .csv files generated by earlier suites, if any file is not present then last suite will fail.
+
+### Usage
+```bash
+pdm run evaluate
+```
+
+### Input Data/QnA pool
+[Json file](../eval_data/question_answer_pair.json)
+
+[Sample QnA set (parquet)](../eval_data/interview_qna_30_per_title.parquet)
+
+Please refer above files for the structure, add new data accordingly.
+
+## Arguments
+**eval_type**: This will control which evaluation, we want to do. Currently we have 3 options.
+1. `consistency` -> Compares model specific answer for QnAs provided in json file
+2. `model` -> Compares set of models based on their response and generates a summary report. For this we can provide additional QnAs in parquet format, along with json file.
+3. `all` -> Both of the above evaluations.
+
+**eval_api_url**: OLS API url. Default is `http://localhost:8080`. If deployed in a cluster, then pass cluster API url.
+
+**eval_api_token_file**: Path to a text file containing OLS API token. Required, if OLS is deployed in cluster.
+
+**eval_scenario**: This is primarily required to identify which pre-defined answers need to be compared. Values can be `with_rag`, `without_rag`. Currently we always do evaluation for the API with rag.
+
+**eval_query_ids**: Option to give set of query ids for evaluation. By default all queries are processed.
+
+**eval_provider_model_id**: We can provide set of provider/model combinations as ids for comparison.
+
+**qna_pool_file**: Applicable only for `model` evaluation. Provide file path to the parquet file having additional QnAs. Default is None.
+
+**eval_out_dir**: Directory, where output csv/json files will be saved.
+
+**eval_metrics**: By default all scores/metrics are calculated, but this decides which scores will be used to create the graph.
+This is a list of metrics. Ex: cosine, euclidean distance, precision/recall/F1 score, answer relevancy score, LLM based similarity score.
+
+**judge_provider / judge_model**: Provider / Model for judge LLM. This is required for LLM based evaluation (answer relevancy score, LLM based similarity score). This needs to be configured correctly through config yaml file. [Sample provider/model configuration](https://github.com/road-core/service/blob/main/examples/rcsconfig.yaml)
+
+**eval_modes**: Apart from OLS api, we may want to evaluate vanilla model or with just OLS parameters/prompt/RAG so that we can have baseline score. This is a list of modes. Ex: vanilla, ols_param, ols_prompt, ols_rag, & ols (actual api).
+
+### Outputs
+Evaluation scripts creates below files.
+- CSV file with response for given provider/model & modes.
+- response evaluation result with scores (for consistency check).
+- Final csv file with all results, json score summary & graph (for model evaluation)
+
+[Evaluation Result](example_result/README.md)
+
+
+# RAG retrieval script
+```
+python -m lightspeed_core_evaluation.evaluation.query_rag
+```
+This is used to generate a .csv file having retrieved chunks for given set of queries with similarity score. This is not part of actual evaluation. But useful to do a spot check to understand the text that we send to LLMs as context (this may explain any deviation in the response)
+
+#### Arguments
+*db-path*: Path to the RAG index
+
+*product-index*: RAG index ID
+
+*model-path*: Path or name of the embedding model
+
+*queries*: Set of queries separated by space. If not passed default queries are used.
+
+*top-k*: How many chunks we want to retrieve. Default is 10.
+
+*output_dir*: To save the .csv file.
\ No newline at end of file
diff --git a/assets/response_eval_flow.png b/archive/assets/response_eval_flow.png
similarity index 100%
rename from assets/response_eval_flow.png
rename to archive/assets/response_eval_flow.png
diff --git a/example_result/README.md b/archive/example_result/README.md
similarity index 96%
rename from example_result/README.md
rename to archive/example_result/README.md
index 98abbdd3..2b1592ac 100644
--- a/example_result/README.md
+++ b/archive/example_result/README.md
@@ -11,7 +11,7 @@
     - (watsonx) ibm/granite-3-2-8b-instruct (API Version: 2025-04-02)
     - (azure) gpt-4o-mini (Model Version: 2024-07-18, API Version: 2024-02-15-preview)
 - Judge provider/model (LLM based eval): (watsonx) llama-3-1-8b-instruct
-- QnA evaluation dataset: [QnAs from OCP doc](../ocp_doc_qna-edited.parquet)
+- QnA evaluation dataset: [QnAs from OCP doc](../../eval_data/ocp_doc_qna-edited.parquet)
 - API run mode: without tool calling (streaming internally)
 - RAG SHA: 56269892dcf5279b9857c04918e8fba587008990b09146e907d7af9303bd6c9e
     - OCP doc: 4.18
diff --git a/example_result/model_evaluation_result-answer_relevancy.png b/archive/example_result/model_evaluation_result-answer_relevancy.png
similarity index 100%
rename from example_result/model_evaluation_result-answer_relevancy.png
rename to archive/example_result/model_evaluation_result-answer_relevancy.png
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diff --git a/example_result/model_evaluation_result-cos_score.png b/archive/example_result/model_evaluation_result-cos_score.png
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diff --git a/src/lightspeed_core_evaluation/utils/response.py b/archive/lightspeed_core_evaluation/utils/response.py
similarity index 100%
rename from src/lightspeed_core_evaluation/utils/response.py
rename to archive/lightspeed_core_evaluation/utils/response.py
diff --git a/src/lightspeed_core_evaluation/utils/score.py b/archive/lightspeed_core_evaluation/utils/score.py
similarity index 100%
rename from src/lightspeed_core_evaluation/utils/score.py
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diff --git a/src/lightspeed_core_evaluation/utils/similarity_score_llm.py b/archive/lightspeed_core_evaluation/utils/similarity_score_llm.py
similarity index 100%
rename from src/lightspeed_core_evaluation/utils/similarity_score_llm.py
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diff --git a/archive/pyproject.toml b/archive/pyproject.toml
new file mode 100644
index 00000000..52279d81
--- /dev/null
+++ b/archive/pyproject.toml
@@ -0,0 +1,75 @@
+[project]
+name = "lightspeed-core-evaluation"
+version = "0.1.0"
+description = "Evaluation tooling for lightspeed-core"
+authors = []
+
+# always generate Python 3.11-compatible code.
+target-version = "py311"
+lint.pydocstyle.convention = "google"
+line-length = 100
+
+dependencies = [
+    "pdm>=2.21.0",
+    "pandas>=2.1.4",
+    "httpx>=0.27.2",
+    "langchain>=0.3.12",
+    "llama-index>=0.12.25",
+    "llama-index-core>=0.12.2",
+    "llama-index-vector-stores-faiss>=0.3.0",
+    "llama-index-embeddings-huggingface>=0.4.0",
+    "ibm-watsonx-ai>=1.3.6",
+    "tqdm>=4.67.1",
+    "llama-index-vector-stores-postgres>=0.4.0",
+    "rouge-score>=0.1.2",
+    "torch==2.7.0+cpu",
+    "road-core @ git+https://github.com/road-core/service.git",
+    "matplotlib>=3.10.1",
+    "ragas>=0.2.15",
+]
+requires-python = ">=3.11.1,<=3.12.8"
+readme = "README.md"
+license = {text = "Apache"}
+
+[dependency-groups]
+dev = [
+    "black>=25.1.0",
+    "mypy>=1.15.0",
+    "ruff>=0.8.0",
+    "pyright>=1.1.401",
+    "pydocstyle>=6.3.0",
+    "pylint>=3.3.2",
+    "pytest>=8.3.2",
+    "pytest-cov>=5.0.0",
+]
+
+[project.scripts]
+evaluate = "lightspeed_core_evaluation.driver:main"
+eval = "lightspeed_core_evaluation.driver:main"
+query_rag = "lightspeed_core_evaluation.query_rag:main"
+
+# The following section is needed only for torch[cpu] variant on Linux,
+# because this variant need to be downloaded from external link, not from
+# standard Python package index:
+#
+[[tool.pdm.source]]
+type = "find_links"
+url = "https://download.pytorch.org/whl/cpu/torch/"
+name = "torch"
+
+[tool.mypy]
+disable_error_code = ["union-attr", "return-value", "arg-type", "import-untyped"]
+ignore_missing_imports = true
+plugins = ["pydantic.mypy"]
+
+[tool.pydantic-mypy]
+init_forbid_extra = true
+init_typed = true
+warn_required_dynamic_aliases = true
+
+[build-system]
+requires = ["pdm-backend"]
+build-backend = "pdm.backend"
+
+[tool.pdm]
+distribution = true
diff --git a/lsc_eval/config/evaluation_data.yaml b/config/evaluation_data.yaml
similarity index 96%
rename from lsc_eval/config/evaluation_data.yaml
rename to config/evaluation_data.yaml
index 2c2bb3c3..32dd10a8 100644
--- a/lsc_eval/config/evaluation_data.yaml
+++ b/config/evaluation_data.yaml
@@ -1,4 +1,4 @@
-# LSC Evaluation Framework - Sample/Mock Data
+# LightSpeed Evaluation Framework - Sample/Mock Data
 
 - conversation_group_id: "conv_group_1"
   description: "conversation group description"
diff --git a/lsc_eval/config/system.yaml b/config/system.yaml
similarity index 98%
rename from lsc_eval/config/system.yaml
rename to config/system.yaml
index 677bcd4f..df2a0c6f 100644
--- a/lsc_eval/config/system.yaml
+++ b/config/system.yaml
@@ -1,4 +1,4 @@
-# LSC Evaluation Framework Configuration
+# LightSpeed Evaluation Framework Configuration
 
 # LLM Configuration
 llm:
diff --git a/lsc_agent_eval/src/lsc_agent_eval/core/utils/judge.py b/lsc_agent_eval/src/lsc_agent_eval/core/utils/judge.py
index 95d9a9eb..f3b91b47 100644
--- a/lsc_agent_eval/src/lsc_agent_eval/core/utils/judge.py
+++ b/lsc_agent_eval/src/lsc_agent_eval/core/utils/judge.py
@@ -99,8 +99,10 @@ def evaluate_response(self, prompt: str) -> Optional[str]:
                 choices = getattr(response, "choices", None)
                 if choices and len(choices) > 0:
                     message = getattr(
-                        choices[0], "message", None
-                    )  # pylint: disable=unsubscriptable-object
+                        choices[0],  # pylint: disable=unsubscriptable-object
+                        "message",
+                        None,
+                    )
                     if message:
                         content = getattr(message, "content", None)
 
diff --git a/lsc_eval/README.md b/lsc_eval/README.md
deleted file mode 100644
index fe985aba..00000000
--- a/lsc_eval/README.md
+++ /dev/null
@@ -1,139 +0,0 @@
-# LSC Evaluation Framework
-
-A comprehensive framework/tool to evaluate GenAI application.
-
-## 🎯 Key Features
-
-- **Multi-Framework Support**: Seamlessly use metrics from Ragas, DeepEval, and custom implementations
-- **Turn & Conversation-Level Evaluation**: Support for both individual queries and multi-turn conversations  
-- **LLM Provider Flexibility**: OpenAI, Anthropic, Watsonx, Azure, Gemini, Ollama via LiteLLM
-- **Flexible Configuration**: Configurable environment & metric metadata
-- **Rich Output**: CSV, JSON, TXT reports + visualization graphs (pass rates, distributions, heatmaps)
-- **Early Validation**: Catch configuration errors before expensive LLM calls
-- **Statistical Analysis**: Statistics for every metric with score distribution analysis
-
-## 🚀 Quick Start
-
-### Installation
-```bash
-# From Git
-uv add git+https://github.com/your-org/lightspeed-evaluation.git#subdirectory=lsc_eval
-# or pip install git+https://github.com/lightspeed-core/lightspeed-evaluation.git#subdirectory=lsc_eval
-
-# Local Development  
-cd lsc_eval && uv sync
-```
-
-### Basic Usage
-```bash
-# Set API key
-export OPENAI_API_KEY="your-key"
-
-# Run evaluation (Create your own data)
-uv run python runner.py --system-config config/system.yaml --eval-data config/evaluation_data.yaml
-```
-
-## 📊 Supported Metrics
-
-### Turn-Level (Single Query)
-- **Ragas**
-  - Response Evaluation
-    - `faithfulness`
-    - `response_relevancy`
-  - Context Evaluation
-    - `context_recall`
-    - `context_relevance`
-    - `context_precision_without_reference`
-    - `context_precision_with_reference`
-- **Custom**
-  - Response Evaluation
-    - `answer_correctness`
-
-### Conversation-Level (Multi-turn)
-- **DeepEval**
-  - `conversation_completeness`
-  - `conversation_relevancy`
-  - `knowledge_retention`
-
-## ⚙️ Configuration
-
-### System Config (`system.yaml`)
-```yaml
-llm:
-  provider: "openai"
-  model: "gpt-4o-mini"
-  temperature: 0.0
-  timeout: 120
-
-metrics_metadata:
-  turn_level:
-    "ragas:faithfulness":
-      threshold: 0.8
-      type: "turn"
-      framework: "ragas"
-  
-  conversation_level:
-    "deepeval:conversation_completeness":
-      threshold: 0.8
-      type: "conversation"
-      framework: "deepeval"
-```
-
-### Evaluation Data (`evaluation_data.yaml`)
-```yaml
-- conversation_group_id: "test_conversation"
-  description: "Sample evaluation"
-  
-  # Turn-level metrics (empty list = skip turn evaluation)
-  turn_metrics:
-    - "ragas:faithfulness"
-    - "custom:answer_correctness"
-  
-  # Turn-level metrics metadata (threshold + other properties)
-  turn_metrics_metadata:
-    "ragas:response_relevancy": 
-      threshold: 0.8
-      weight: 1.0
-    "custom:answer_correctness": 
-      threshold: 0.75
-  
-  # Conversation-level metrics (empty list = skip conversation evaluation)   
-  conversation_metrics:
-    - "deepeval:conversation_completeness"
-  
-  turns:
-    - turn_id: 1
-      query: "What is OpenShift?"
-      response: "Red Hat OpenShift powers the entire application lifecycle...."
-      contexts:
-        - content: "Red Hat OpenShift powers...."
-      expected_response: "Red Hat OpenShift...."
-```
-
-## 📈 Output & Visualization
-
-### Generated Reports
-- **CSV**: Detailed results with status, scores, reasons
-- **JSON**: Summary statistics with score distributions
-- **TXT**: Human-readable summary
-- **PNG**: 4 visualization types (pass rates, score distributions, heatmaps, status breakdown)
-
-### Key Metrics in Output
-- **PASS/FAIL/ERROR**: Status based on thresholds
-- **Actual Reasons**: DeepEval provides LLM-generated explanations, Custom metrics provide detailed reasoning
-- **Score Statistics**: Mean, median, standard deviation, min/max for every metric
-
-### Development Tools
-```bash
-uv run black .
-uv run ruff check .
-uv run mypy .
-uv run pyright .
-uv run pylint .
-```
-
-## 📄 License & Contributing
-
-This project is licensed under the Apache License 2.0. See the LICENSE file for details.
-
-Contributions welcome - see development setup above for code quality tools.
diff --git a/lsc_eval/pyproject.toml b/lsc_eval/pyproject.toml
deleted file mode 100644
index 87a93eab..00000000
--- a/lsc_eval/pyproject.toml
+++ /dev/null
@@ -1,56 +0,0 @@
-[project]
-name = "lsc_eval"
-version = "0.1.0"
-description = "LSC Evaluation Framework"
-authors = []
-requires-python = ">=3.11,<3.13"
-readme = "README.md"
-license = {text = "Apache"}
-
-dependencies = [
-    "ragas>=0.3.0",
-    "deepeval>=1.3.0",
-    "litellm>=1.0.0",
-    "pydantic>=2.0.0",
-    "pyyaml>=6.0",
-    "pandas>=1.5.0",
-    "datasets>=2.0.0",
-    "matplotlib>=3.5.0",
-    "seaborn>=0.11.0",
-    "numpy>=1.23.0",
-    "torch==2.7.0",
-]
-
-[dependency-groups]
-dev = [
-    "black>=25.1.0",
-    "mypy>=1.15.0",
-    "ruff>=0.8.0",
-    "pyright>=1.1.401",
-    "pydocstyle>=6.3.0",
-    "pylint>=3.3.2",
-    "pytest>=8.3.2",
-    "pytest-cov>=5.0.0",
-]
-
-
-[project.urls]
-"Homepage" = "https://github.com/lightspeed-core/lightspeed-evaluation"
-"Bug Tracker" = "https://github.com/lightspeed-core/lightspeed-evaluation/issues"
-
-[build-system]
-requires = ["hatchling"]
-build-backend = "hatchling.build"
-
-
-[tool.ruff]
-# always generate Python 3.11-compatible code.
-target-version = "py311"
-line-length = 100
-
-[tool.ruff.lint.pydocstyle]
-convention = "google" 
-
-[tool.black]
-line-length = 100
-target-version = ['py311']
diff --git a/lsc_eval/src/lsc_eval/__init__.py b/lsc_eval/src/lsc_eval/__init__.py
deleted file mode 100644
index 0c178750..00000000
--- a/lsc_eval/src/lsc_eval/__init__.py
+++ /dev/null
@@ -1,25 +0,0 @@
-"""LSC Evaluation Framework / Tool."""
-
-from .core import (
-    ConfigLoader,
-    DataValidator,
-    EvaluationData,
-    EvaluationResult,
-    SystemConfig,
-    TurnData,
-)
-from .evaluation_engine import EvaluationEngine
-from .llm_managers.llm_manager import LLMManager
-from .output.output_handler import OutputHandler
-
-__all__ = [
-    "SystemConfig",
-    "EvaluationData",
-    "TurnData",
-    "ConfigLoader",
-    "DataValidator",
-    "LLMManager",
-    "EvaluationEngine",
-    "EvaluationResult",
-    "OutputHandler",
-]
diff --git a/lsc_eval/src/lsc_eval/core/__init__.py b/lsc_eval/src/lsc_eval/core/__init__.py
deleted file mode 100644
index bbf38734..00000000
--- a/lsc_eval/src/lsc_eval/core/__init__.py
+++ /dev/null
@@ -1,22 +0,0 @@
-"""Core functionality - Configuration, data validation, and models."""
-
-from .config_loader import (
-    ConfigLoader,
-    SystemConfig,
-    setup_environment_variables,
-    validate_metrics,
-)
-from .data_validator import DataValidator
-from .models import EvaluationData, EvaluationResult, LLMConfig, TurnData
-
-__all__ = [
-    "ConfigLoader",
-    "SystemConfig",
-    "validate_metrics",
-    "DataValidator",
-    "setup_environment_variables",
-    "EvaluationData",
-    "EvaluationResult",
-    "LLMConfig",
-    "TurnData",
-]
diff --git a/lsc_eval/src/lsc_eval/llm_managers/__init__.py b/lsc_eval/src/lsc_eval/llm_managers/__init__.py
deleted file mode 100644
index 52c921e4..00000000
--- a/lsc_eval/src/lsc_eval/llm_managers/__init__.py
+++ /dev/null
@@ -1,7 +0,0 @@
-"""LLM Managers for different evaluation frameworks."""
-
-from .deepeval_llm import DeepEvalLLMManager
-from .llm_manager import LLMManager
-from .ragas_llm import RagasLLMManager
-
-__all__ = ["LLMManager", "RagasLLMManager", "DeepEvalLLMManager"]
diff --git a/lsc_eval/src/lsc_eval/metrics/__init__.py b/lsc_eval/src/lsc_eval/metrics/__init__.py
deleted file mode 100644
index f89175fa..00000000
--- a/lsc_eval/src/lsc_eval/metrics/__init__.py
+++ /dev/null
@@ -1,7 +0,0 @@
-"""Evaluation metrics for different frameworks."""
-
-from .custom_metrics import CustomMetrics
-from .deepeval_metrics import DeepEvalMetrics
-from .ragas_metrics import RagasMetrics
-
-__all__ = ["RagasMetrics", "DeepEvalMetrics", "CustomMetrics"]
diff --git a/lsc_eval/uv.lock b/lsc_eval/uv.lock
deleted file mode 100644
index 3f3473eb..00000000
--- a/lsc_eval/uv.lock
+++ /dev/null
@@ -1,2949 +0,0 @@
-version = 1
-revision = 3
-requires-python = ">=3.11, <3.13"
-resolution-markers = [
-    "python_full_version >= '3.12'",
-    "python_full_version < '3.12'",
-]
-
-[[package]]
-name = "aiohappyeyeballs"
-version = "2.6.1"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
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-[[package]]
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diff --git a/pyproject.toml b/pyproject.toml
index 131de681..b4904201 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,34 +1,33 @@
 [project]
-name = "lightspeed-core-evaluation"
+name = "lightspeed-evaluation"
 version = "0.1.0"
-description = "Evaluation tooling for lightspeed-core"
+description = "LSC Evaluation Framework - Comprehensive evaluation tooling for GenAI applications"
 authors = []
-
-# always generate Python 3.11-compatible code.
-target-version = "py311"
-lint.pydocstyle.convention = "google"
-line-length = 100
+requires-python = ">=3.11,<3.13"
+readme = "README.md"
+license = {text = "Apache"}
 
 dependencies = [
+    # Core evaluation framework dependencies
+    "ragas>=0.3.0",
+    "deepeval>=1.3.0",
+    "litellm>=1.0.0",
+    "pydantic>=2.0.0",
+    "pyyaml>=6.0",
     "pandas>=2.1.4",
-    "httpx==0.27.2",
-    "langchain>=0.3.12",
-    "llama-index>=0.12.25",
-    "llama-index-core>=0.12.2",
-    "llama-index-vector-stores-faiss>=0.3.0",
-    "llama-index-embeddings-huggingface>=0.4.0",
-    "ibm-watsonx-ai>=1.3.6",
-    "tqdm>=4.67.1",
-    "llama-index-vector-stores-postgres>=0.4.0",
-    "rouge-score>=0.1.2",
+    "datasets>=2.0.0",
+    "matplotlib>=3.5.0",
+    "seaborn>=0.11.0",
+    "numpy>=1.23.0",
     "torch==2.7.0",
-    "matplotlib>=3.10.1",
-    "ragas>=0.2.15",
+    # Agent evaluation dependencies (for future integration)
+    "httpx>=0.27.2",
+    "tqdm>=4.67.1",
+    # Generate answers dependencies
+    "click>=8.0.0",
+    "diskcache>=5.6.3",
     "tenacity>=9.1.2",
 ]
-requires-python = ">=3.11.1,<=3.12.8"
-readme = "README.md"
-license = {text = "Apache"}
 
 [dependency-groups]
 dev = [
@@ -43,9 +42,7 @@ dev = [
 ]
 
 [project.scripts]
-evaluate = "lightspeed_core_evaluation.driver:main"
-eval = "lightspeed_core_evaluation.driver:main"
-query_rag = "lightspeed_core_evaluation.query_rag:main"
+lightspeed-eval = "lightspeed_evaluation.runner.evaluation:main"
 generate_answers = "generate_answers.generate_answers:main"
 
 # Note: torch[cpu] variant configuration removed for uv compatibility
@@ -64,4 +61,5 @@ warn_required_dynamic_aliases = true
 [build-system]
 requires = ["hatchling"]
 build-backend = "hatchling.build"
-
+[tool.hatch.build.targets.wheel]
+packages = ["src/lightspeed_evaluation"]
diff --git a/src/lightspeed_evaluation/__init__.py b/src/lightspeed_evaluation/__init__.py
new file mode 100644
index 00000000..723a1d83
--- /dev/null
+++ b/src/lightspeed_evaluation/__init__.py
@@ -0,0 +1,55 @@
+"""
+LightSpeed Evaluation Framework.
+
+Main components:
+- EvaluationDriver: Runs complete evaluation
+- Runner: Simple runner for command-line usage
+- Core modules organized by functionality (config, llm, metrics, output)
+
+Usage:
+    from lightspeed_evaluation import EvaluationDriver, ConfigLoader
+    loader = ConfigLoader()
+    driver = EvaluationDriver(loader)
+    results = driver.run_evaluation(evaluation_data)
+"""
+
+__version__ = "0.1.0"
+
+# Main driver
+from .drivers.evaluation import EvaluationDriver
+
+# Core components
+from .core.llm import LLMManager
+from .core.config import (
+    ConfigLoader,
+    SystemConfig,
+    EvaluationData,
+    TurnData,
+    EvaluationResult,
+    DataValidator,
+)
+from .core.config import LLMConfig
+from .core.metrics import RagasMetrics, DeepEvalMetrics, CustomMetrics
+
+# Output handling
+from .core.output import OutputHandler, GraphGenerator
+
+__all__ = [
+    # Main components
+    "EvaluationDriver",
+    "LLMManager",
+    "ConfigLoader",
+    "SystemConfig",
+    "EvaluationData",
+    "TurnData",
+    "EvaluationResult",
+    "DataValidator",
+    "LLMConfig",
+    # Metrics
+    "RagasMetrics",
+    "DeepEvalMetrics",
+    "CustomMetrics",
+    # Output handling
+    "OutputHandler",
+    "GraphGenerator",
+]
diff --git a/src/lightspeed_evaluation/core/__init__.py b/src/lightspeed_evaluation/core/__init__.py
new file mode 100644
index 00000000..6abe0ce7
--- /dev/null
+++ b/src/lightspeed_evaluation/core/__init__.py
@@ -0,0 +1,28 @@
+"""Core functionality - Components for evaluation."""
+
+# Configuration
+from .config import (
+    ConfigLoader,
+    SystemConfig,
+    EvaluationData,
+    setup_environment_variables,
+    DataValidator,
+)
+from .config import EvaluationResult, TurnData, LLMConfig
+
+# LLM management
+from .llm import LLMManager
+
+__all__ = [
+    # Configuration & data
+    "ConfigLoader",
+    "SystemConfig",
+    "EvaluationData",
+    "setup_environment_variables",
+    "DataValidator",
+    "EvaluationResult",
+    "TurnData",
+    "LLMConfig",
+    # LLM management
+    "LLMManager",
+]
diff --git a/src/lightspeed_evaluation/core/config/__init__.py b/src/lightspeed_evaluation/core/config/__init__.py
new file mode 100644
index 00000000..60ab7dcf
--- /dev/null
+++ b/src/lightspeed_evaluation/core/config/__init__.py
@@ -0,0 +1,16 @@
+"""Configuration loading and models for Evaluation Framework."""
+
+from .loader import ConfigLoader, setup_environment_variables, SystemConfig
+from .models import EvaluationData, EvaluationResult, TurnData, LLMConfig
+from .validator import DataValidator
+
+__all__ = [
+    "ConfigLoader",
+    "setup_environment_variables",
+    "SystemConfig",
+    "EvaluationData",
+    "EvaluationResult",
+    "TurnData",
+    "LLMConfig",
+    "DataValidator",
+]
diff --git a/lsc_eval/src/lsc_eval/core/config_loader.py b/src/lightspeed_evaluation/core/config/loader.py
similarity index 98%
rename from lsc_eval/src/lsc_eval/core/config_loader.py
rename to src/lightspeed_evaluation/core/config/loader.py
index 035663f9..eebb7dfd 100644
--- a/lsc_eval/src/lsc_eval/core/config_loader.py
+++ b/src/lightspeed_evaluation/core/config/loader.py
@@ -1,4 +1,4 @@
-"""Configuration loading for LSC Evaluation Framework."""
+"""Configuration loading for Evaluation Framework."""
 
 import logging
 import os
@@ -97,7 +97,7 @@ def setup_logging(logging_config: Dict[str, Any]) -> logging.Logger:
             )
 
     # Get logger for our application
-    logger = logging.getLogger("lsc_eval")
+    logger = logging.getLogger("lightspeed_evaluation")
     logger.setLevel(source_level)
 
     logger.debug(
diff --git a/lsc_eval/src/lsc_eval/core/models.py b/src/lightspeed_evaluation/core/config/models.py
similarity index 83%
rename from lsc_eval/src/lsc_eval/core/models.py
rename to src/lightspeed_evaluation/core/config/models.py
index 7582f27d..e52a5407 100644
--- a/lsc_eval/src/lsc_eval/core/models.py
+++ b/src/lightspeed_evaluation/core/config/models.py
@@ -1,4 +1,4 @@
-"""Data models for LSC Evaluation Framework."""
+"""Data models for Evaluation Framework."""
 
 from typing import Any, Dict, List, Optional
 
@@ -170,30 +170,37 @@ def validate_execution_time(cls, v: float) -> float:
 
 
 class LLMConfig(BaseModel):
-    """LLM Configuration with validation."""
+    """LLM configuration from system configuration."""
 
-    model_name: str = Field(..., description="The model name to use")
-    api_base: Optional[str] = Field(None, description="Custom API base URL")
-    api_key: Optional[str] = Field(None, description="API key for the model")
-    temperature: float = Field(
-        0.0, ge=0.0, le=2.0, description="Temperature for sampling"
-    )
-    max_tokens: Optional[int] = Field(
-        None, ge=1, description="Maximum tokens to generate"
-    )
-    timeout: Optional[int] = Field(None, ge=1, description="Request timeout in seconds")
-    num_retries: int = Field(
-        3, ge=0, description="Number of retries for failed requests"
+    provider: str = Field(
+        ..., description="Provider name, e.g., openai, azure, watsonx"
     )
+    model: str = Field(..., description="Model identifier or deployment name")
+    temperature: float = Field(0.0, ge=0.0, le=2.0, description="Sampling temperature")
+    max_tokens: int = Field(512, ge=1, description="Maximum tokens in response")
+    timeout: int = Field(300, ge=1, description="Request timeout in seconds")
+    num_retries: int = Field(3, ge=0, description="Retry attempts for failed requests")
 
-    @field_validator("model_name")
+    @field_validator("provider", "model")
     @classmethod
-    def validate_model_name(cls, v: str) -> str:
-        """Validate model name is non-empty."""
-        if not v or not v.strip():
-            raise ValueError("Model name cannot be empty")
+    def _validate_non_empty(cls, v: str) -> str:
+        """Validate provider and model are non-empty strings."""
+        if not v or not isinstance(v, str) or not v.strip():
+            raise ValueError("Value cannot be empty")
         return v.strip()
 
+    @classmethod
+    def from_dict(cls, config_dict: Dict[str, Any]) -> "LLMConfig":
+        """Create LLMConfig from a plain dictionary."""
+        return cls(
+            provider=config_dict.get("provider", "openai"),
+            model=config_dict.get("model", "gpt-4o-mini"),
+            temperature=config_dict.get("temperature", 0.0),
+            max_tokens=config_dict.get("max_tokens", 512),
+            timeout=config_dict.get("timeout", 300),
+            num_retries=config_dict.get("num_retries", 3),
+        )
+
 
 # System configuration models
 class EvaluationSystemConfig(BaseModel):
diff --git a/lsc_eval/src/lsc_eval/core/data_validator.py b/src/lightspeed_evaluation/core/config/validator.py
similarity index 97%
rename from lsc_eval/src/lsc_eval/core/data_validator.py
rename to src/lightspeed_evaluation/core/config/validator.py
index 83128590..fd262c42 100644
--- a/lsc_eval/src/lsc_eval/core/data_validator.py
+++ b/src/lightspeed_evaluation/core/config/validator.py
@@ -4,7 +4,7 @@
 
 import yaml
 
-from .config_loader import CONVERSATION_LEVEL_METRICS, TURN_LEVEL_METRICS
+from .loader import CONVERSATION_LEVEL_METRICS, TURN_LEVEL_METRICS
 from .models import EvaluationData
 
 
diff --git a/src/lightspeed_evaluation/core/llm/__init__.py b/src/lightspeed_evaluation/core/llm/__init__.py
new file mode 100644
index 00000000..f41721ef
--- /dev/null
+++ b/src/lightspeed_evaluation/core/llm/__init__.py
@@ -0,0 +1,14 @@
+"""LLM management for Evaluation Framework."""
+
+from .manager import LLMManager, LLMError
+from .deepeval import DeepEvalLLMManager
+from .ragas import RagasLLMManager
+from ..config import LLMConfig
+
+__all__ = [
+    "LLMManager",
+    "LLMConfig",
+    "LLMError",
+    "DeepEvalLLMManager",
+    "RagasLLMManager",
+]
diff --git a/lsc_eval/src/lsc_eval/llm_managers/deepeval_llm.py b/src/lightspeed_evaluation/core/llm/deepeval.py
similarity index 100%
rename from lsc_eval/src/lsc_eval/llm_managers/deepeval_llm.py
rename to src/lightspeed_evaluation/core/llm/deepeval.py
diff --git a/lsc_eval/src/lsc_eval/llm_managers/llm_manager.py b/src/lightspeed_evaluation/core/llm/manager.py
similarity index 88%
rename from lsc_eval/src/lsc_eval/llm_managers/llm_manager.py
rename to src/lightspeed_evaluation/core/llm/manager.py
index 66aa03ff..85f32d98 100644
--- a/lsc_eval/src/lsc_eval/llm_managers/llm_manager.py
+++ b/src/lightspeed_evaluation/core/llm/manager.py
@@ -1,38 +1,15 @@
 """LLM Manager - Generic LLM configuration, validation, and parameter provider."""
 
 import os
-from dataclasses import dataclass
 from typing import Any, Dict
 
+from ..config import LLMConfig
+
 
 class LLMError(Exception):
     """LLM configuration error."""
 
 
-@dataclass
-class LLMConfig:
-    """LLM configuration from system configuration."""
-
-    provider: str
-    model: str
-    temperature: float = 0.0
-    max_tokens: int = 512
-    timeout: int = 300
-    num_retries: int = 3
-
-    @classmethod
-    def from_dict(cls, config_dict: Dict[str, Any]) -> "LLMConfig":
-        """Create config from dictionary."""
-        return cls(
-            provider=config_dict.get("provider", "openai"),
-            model=config_dict.get("model", "gpt-4o-mini"),
-            temperature=config_dict.get("temperature", 0.0),
-            max_tokens=config_dict.get("max_tokens", 512),
-            timeout=config_dict.get("timeout", 300),
-            num_retries=config_dict.get("num_retries", 3),
-        )
-
-
 class LLMManager:
     """
     Generic LLM Manager for all use cases (Ragas, DeepEval, Custom metrics).
diff --git a/lsc_eval/src/lsc_eval/llm_managers/ragas_llm.py b/src/lightspeed_evaluation/core/llm/ragas.py
similarity index 100%
rename from lsc_eval/src/lsc_eval/llm_managers/ragas_llm.py
rename to src/lightspeed_evaluation/core/llm/ragas.py
diff --git a/src/lightspeed_evaluation/core/metrics/__init__.py b/src/lightspeed_evaluation/core/metrics/__init__.py
new file mode 100644
index 00000000..8f959693
--- /dev/null
+++ b/src/lightspeed_evaluation/core/metrics/__init__.py
@@ -0,0 +1,7 @@
+"""Evaluation metrics for different frameworks."""
+
+from .custom import CustomMetrics
+from .deepeval import DeepEvalMetrics
+from .ragas import RagasMetrics
+
+__all__ = ["RagasMetrics", "DeepEvalMetrics", "CustomMetrics"]
diff --git a/lsc_eval/src/lsc_eval/metrics/custom_metrics.py b/src/lightspeed_evaluation/core/metrics/custom.py
similarity index 98%
rename from lsc_eval/src/lsc_eval/metrics/custom_metrics.py
rename to src/lightspeed_evaluation/core/metrics/custom.py
index 23ccca76..cd2928c9 100644
--- a/lsc_eval/src/lsc_eval/metrics/custom_metrics.py
+++ b/src/lightspeed_evaluation/core/metrics/custom.py
@@ -6,9 +6,9 @@
 import litellm
 from pydantic import BaseModel, Field
 
-from ..core.models import TurnData
-from ..llm_managers.llm_manager import LLMManager
-from ..output.utils import EvaluationScope
+from ..config import TurnData
+from ..llm.manager import LLMManager
+from ..output.statistics import EvaluationScope
 
 
 class EvaluationPromptParams(BaseModel):
diff --git a/lsc_eval/src/lsc_eval/metrics/deepeval_metrics.py b/src/lightspeed_evaluation/core/metrics/deepeval.py
similarity index 96%
rename from lsc_eval/src/lsc_eval/metrics/deepeval_metrics.py
rename to src/lightspeed_evaluation/core/metrics/deepeval.py
index 21db5029..20d157fd 100644
--- a/lsc_eval/src/lsc_eval/metrics/deepeval_metrics.py
+++ b/src/lightspeed_evaluation/core/metrics/deepeval.py
@@ -10,10 +10,10 @@
 from deepeval.test_case import ConversationalTestCase
 from deepeval.test_case import Turn as DeepEvalTurn
 
-from ..core.models import TurnData
-from ..llm_managers.deepeval_llm import DeepEvalLLMManager
-from ..llm_managers.llm_manager import LLMManager
-from ..output.utils import EvaluationScope
+from ..config import TurnData
+from ..llm.deepeval import DeepEvalLLMManager
+from ..llm.manager import LLMManager
+from ..output.statistics import EvaluationScope
 
 
 class DeepEvalMetrics:
diff --git a/lsc_eval/src/lsc_eval/metrics/ragas_metrics.py b/src/lightspeed_evaluation/core/metrics/ragas.py
similarity index 97%
rename from lsc_eval/src/lsc_eval/metrics/ragas_metrics.py
rename to src/lightspeed_evaluation/core/metrics/ragas.py
index 1f0084ea..27993188 100644
--- a/lsc_eval/src/lsc_eval/metrics/ragas_metrics.py
+++ b/src/lightspeed_evaluation/core/metrics/ragas.py
@@ -13,10 +13,10 @@
     ResponseRelevancy,
 )
 
-from ..core.models import TurnData
-from ..llm_managers.llm_manager import LLMManager
-from ..llm_managers.ragas_llm import RagasLLMManager
-from ..output.utils import EvaluationScope
+from ..config import TurnData
+from ..llm.manager import LLMManager
+from ..llm.ragas import RagasLLMManager
+from ..output.statistics import EvaluationScope
 
 
 # Decide if Dataset will be used or not ?
diff --git a/lsc_eval/src/lsc_eval/output/__init__.py b/src/lightspeed_evaluation/core/output/__init__.py
similarity index 77%
rename from lsc_eval/src/lsc_eval/output/__init__.py
rename to src/lightspeed_evaluation/core/output/__init__.py
index 65789601..1044245e 100644
--- a/lsc_eval/src/lsc_eval/output/__init__.py
+++ b/src/lightspeed_evaluation/core/output/__init__.py
@@ -1,6 +1,6 @@
 """Output handling - Reports and visualization."""
 
-from .output_handler import OutputHandler
+from .generator import OutputHandler
 from .visualization import GraphGenerator
 
 __all__ = ["OutputHandler", "GraphGenerator"]
diff --git a/lsc_eval/src/lsc_eval/output/output_handler.py b/src/lightspeed_evaluation/core/output/generator.py
similarity index 98%
rename from lsc_eval/src/lsc_eval/output/output_handler.py
rename to src/lightspeed_evaluation/core/output/generator.py
index adf24da2..f4c0bcf2 100644
--- a/lsc_eval/src/lsc_eval/output/output_handler.py
+++ b/src/lightspeed_evaluation/core/output/generator.py
@@ -6,9 +6,9 @@
 from pathlib import Path
 from typing import Any, Dict, List, Optional
 
-from ..core.config_loader import DEFAULT_CSV_COLUMNS
-from ..core.models import EvaluationResult
-from .utils import calculate_basic_stats, calculate_detailed_stats
+from ..config.loader import DEFAULT_CSV_COLUMNS
+from ..config import EvaluationResult
+from .statistics import calculate_basic_stats, calculate_detailed_stats
 from .visualization import GraphGenerator
 
 
diff --git a/lsc_eval/src/lsc_eval/output/utils.py b/src/lightspeed_evaluation/core/output/statistics.py
similarity index 98%
rename from lsc_eval/src/lsc_eval/output/utils.py
rename to src/lightspeed_evaluation/core/output/statistics.py
index 0c0d5daa..651ab5dc 100644
--- a/lsc_eval/src/lsc_eval/output/utils.py
+++ b/src/lightspeed_evaluation/core/output/statistics.py
@@ -4,7 +4,7 @@
 from dataclasses import dataclass
 from typing import Any, Dict, List, Optional
 
-from ..core.models import EvaluationResult, TurnData
+from ..config import EvaluationResult, TurnData
 
 
 @dataclass
diff --git a/lsc_eval/src/lsc_eval/output/visualization.py b/src/lightspeed_evaluation/core/output/visualization.py
similarity index 98%
rename from lsc_eval/src/lsc_eval/output/visualization.py
rename to src/lightspeed_evaluation/core/output/visualization.py
index c6348134..f799419f 100644
--- a/lsc_eval/src/lsc_eval/output/visualization.py
+++ b/src/lightspeed_evaluation/core/output/visualization.py
@@ -10,8 +10,8 @@
 import seaborn as sns
 from matplotlib.colors import BASE_COLORS
 
-from ..core.models import EvaluationResult
-from .utils import calculate_basic_stats, calculate_detailed_stats
+from ..config import EvaluationResult
+from .statistics import calculate_basic_stats, calculate_detailed_stats
 
 
 class GraphGenerator:
@@ -29,7 +29,7 @@ def __init__(
         self.graphs_dir.mkdir(parents=True, exist_ok=True)
         self.figsize = figsize if figsize else [12, 8]
         self.dpi = dpi
-        self.logger = logging.getLogger("lsc_eval.GraphGenerator")
+        self.logger = logging.getLogger("lightspeed_evaluation.GraphGenerator")
 
         # Set basic matplotlib settings
         plt.rcParams["figure.facecolor"] = "white"
diff --git a/src/lightspeed_evaluation/drivers/__init__.py b/src/lightspeed_evaluation/drivers/__init__.py
new file mode 100644
index 00000000..ac90111a
--- /dev/null
+++ b/src/lightspeed_evaluation/drivers/__init__.py
@@ -0,0 +1,5 @@
+"""Evaluation drivers for LightSpeed Evaluation Framework."""
+
+from .evaluation import EvaluationDriver
+
+__all__ = ["EvaluationDriver"]
diff --git a/lsc_eval/src/lsc_eval/evaluation_engine.py b/src/lightspeed_evaluation/drivers/evaluation.py
similarity index 95%
rename from lsc_eval/src/lsc_eval/evaluation_engine.py
rename to src/lightspeed_evaluation/drivers/evaluation.py
index 1c0ceebd..04e5209f 100644
--- a/lsc_eval/src/lsc_eval/evaluation_engine.py
+++ b/src/lightspeed_evaluation/drivers/evaluation.py
@@ -1,5 +1,5 @@
 """
-Evaluation Engine - Main evaluation controller.
+Evaluation Driver - Main evaluation controller.
 
 Controls the evaluation flow through conversations & turns
 """
@@ -7,18 +7,18 @@
 import time
 from typing import Any, Dict, List, Optional, Tuple, Union
 
-from .core import (
+from ..core.config import (
     ConfigLoader,
     DataValidator,
     EvaluationData,
     EvaluationResult,
     TurnData,
 )
-from .llm_managers.llm_manager import LLMManager
-from .metrics.custom_metrics import CustomMetrics
-from .metrics.deepeval_metrics import DeepEvalMetrics
-from .metrics.ragas_metrics import RagasMetrics
-from .output.utils import EvaluationScope
+from ..core.llm.manager import LLMManager
+from ..core.metrics.custom import CustomMetrics
+from ..core.metrics.deepeval import DeepEvalMetrics
+from ..core.metrics.ragas import RagasMetrics
+from ..core.output.statistics import EvaluationScope
 
 
 class EvaluationRequest:
@@ -115,9 +115,9 @@ def get_supported_frameworks(self) -> List[str]:
         return list(self.handlers.keys())
 
 
-class EvaluationEngine:
+class EvaluationDriver:
     """
-    Main evaluation engine - orchestrates the evaluation process.
+    Main evaluation driver - orchestrates the evaluation process.
 
     Responsibilities:
     - Data validation
@@ -127,7 +127,7 @@ class EvaluationEngine:
     """
 
     def __init__(self, config_loader: ConfigLoader):
-        """Initialize evaluation engine with config."""
+        """Initialize evaluation driver with config."""
         self.config_loader = config_loader
         self.data_validator = DataValidator()
         self.results: List[EvaluationResult] = []
@@ -137,7 +137,7 @@ def __init__(self, config_loader: ConfigLoader):
         llm_manager = LLMManager.from_system_config(system_config_dict)
         self.metrics_manager = MetricsManager(llm_manager)
 
-        print("✅ Evaluation Engine initialized")
+        print("✅ Evaluation Driver initialized")
 
     def validate_data(self, evaluation_data: List[EvaluationData]) -> bool:
         """Validate evaluation data using data validator."""
diff --git a/src/lightspeed_evaluation/runner/__init__.py b/src/lightspeed_evaluation/runner/__init__.py
new file mode 100644
index 00000000..7bd4f89c
--- /dev/null
+++ b/src/lightspeed_evaluation/runner/__init__.py
@@ -0,0 +1,5 @@
+"""Runner/CLI module for LightSpeed Evaluation Framework."""
+
+from .evaluation import main, run_evaluation
+
+__all__ = ["main", "run_evaluation"]
diff --git a/lsc_eval/src/lsc_eval/runner.py b/src/lightspeed_evaluation/runner/evaluation.py
similarity index 77%
rename from lsc_eval/src/lsc_eval/runner.py
rename to src/lightspeed_evaluation/runner/evaluation.py
index 6acebe05..88d8e6c8 100644
--- a/lsc_eval/src/lsc_eval/runner.py
+++ b/src/lightspeed_evaluation/runner/evaluation.py
@@ -1,15 +1,4 @@
-"""
-LSC Evaluation Framework - Main Evaluation Runner.
-
-Simple interface that uses EvaluationEngine as the core controller.
-
-Usage:
-    python -m runner --system-config config/system.yaml --eval-data config/evaluation_data.yaml
-
-Or programmatically:
-    from runner import run_evaluation
-    results = run_evaluation("config/system.yaml", "config/evaluation_data.yaml")
-"""
+"""LightSpeed Evaluation Framework - Main Evaluation Runner."""
 
 import argparse
 import sys
@@ -17,16 +6,17 @@
 from pathlib import Path
 from typing import Dict, Optional
 
-from lsc_eval import ConfigLoader, DataValidator, EvaluationEngine, OutputHandler
-from lsc_eval.core import setup_environment_variables
-from lsc_eval.output.utils import calculate_basic_stats
+from ..core.config import ConfigLoader, DataValidator, setup_environment_variables
+from ..core.output import OutputHandler
+from ..core.output.statistics import calculate_basic_stats
+from ..drivers.evaluation import EvaluationDriver
 
 
 def run_evaluation(
     system_config_path: str, evaluation_data_path: str, output_dir: Optional[str] = None
 ) -> Optional[Dict[str, int]]:
     """
-    Run the complete evaluation pipeline using EvaluationEngine.
+    Run the complete evaluation pipeline using EvaluationDriver.
 
     Args:
         system_config_path: Path to system.yaml
@@ -36,7 +26,7 @@ def run_evaluation(
     Returns:
         dict: Summary statistics with keys TOTAL, PASS, FAIL, ERROR
     """
-    print("🚀 LSC Evaluation Framework")
+    print("🚀 LightSpeed Evaluation Framework")
     print("=" * 50)
 
     try:
@@ -53,13 +43,13 @@ def run_evaluation(
         )
         print(f"✅ Evaluation data: {len(evaluation_data)} conversation groups")
 
-        # Step 2: Initialize evaluation engine (core controller)
-        print("\n⚙️ Initializing Evaluation Engine...")
-        engine = EvaluationEngine(loader)
+        # Step 2: Initialize evaluation driver (core controller)
+        print("\n⚙️ Initializing Evaluation Driver...")
+        driver = EvaluationDriver(loader)
 
-        # Step 3: Run evaluation (engine controls the flow)
+        # Step 3: Run evaluation (driver controls the flow)
         print("\n🔄 Running Evaluation...")
-        results = engine.run_evaluation(evaluation_data)
+        results = driver.run_evaluation(evaluation_data)
 
         # Step 4: Generate reports
         print("\n📊 Generating Reports...")
@@ -104,7 +94,9 @@ def run_evaluation(
 
 def main() -> int:
     """Command line interface."""
-    parser = argparse.ArgumentParser(description="LSC Evaluation Framework / Tool")
+    parser = argparse.ArgumentParser(
+        description="LightSpeed Evaluation Framework / Tool",
+    )
     parser.add_argument(
         "--system-config",
         default="config/system.yaml",
diff --git a/uv.lock b/uv.lock
index ef9e514c..3965ce35 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,20 +1,11 @@
 version = 1
 revision = 3
-requires-python = ">=3.11.1, <=3.12.8"
+requires-python = ">=3.11, <3.13"
 resolution-markers = [
     "python_full_version >= '3.12'",
     "python_full_version < '3.12'",
 ]
 
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-version = "2.3.1"
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-]
-
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
@@ -89,24 +80,30 @@ wheels = [
 ]
 
 [[package]]
-name = "aiosqlite"
-version = "0.21.0"
+name = "annotated-types"
+version = "0.7.0"
 source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "typing-extensions" },
-]
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+    { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
 [[package]]
-name = "annotated-types"
-version = "0.7.0"
+name = "anthropic"
+version = "0.64.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/ee/67/531ea369ba64dcff5ec9c3402f9f51bf748cec26dde048a2f973a4eea7f5/annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89", size = 16081, upload-time = "2024-05-20T21:33:25.928Z" }
+dependencies = [
+    { name = "anyio" },
+    { name = "distro" },
+    { name = "httpx" },
+    { name = "jiter" },
+    { name = "pydantic" },
+    { name = "sniffio" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/d8/4f/f2b880cba1a76f3acc7d5eb2ae217632eac1b8cef5ed3027493545c59eba/anthropic-0.64.0.tar.gz", hash = "sha256:3d496c91a63dff64f451b3e8e4b238a9640bf87b0c11d0b74ddc372ba5a3fe58", size = 427893, upload-time = "2025-08-13T17:09:49.915Z" }
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+    { url = "https://files.pythonhosted.org/packages/a9/b2/2d268bcd5d6441df9dc0ebebc67107657edb8b0150d3fda1a5b81d1bec45/anthropic-0.64.0-py3-none-any.whl", hash = "sha256:6f5f7d913a6a95eb7f8e1bda4e75f76670e8acd8d4cd965e02e2a256b0429dd1", size = 297244, upload-time = "2025-08-13T17:09:47.908Z" },
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@@ -175,32 +148,12 @@ wheels = [
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