mirror of
https://github.com/qodo-ai/pr-agent.git
synced 2025-07-03 04:10:49 +08:00
Tal
@ -30,50 +30,36 @@ model="" # the OpenAI model you've deployed on Azure (e.g. gpt-4o)
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fallback_models=["..."]
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```
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### Hugging Face
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### Ollama
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**Local**
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You can run Hugging Face models locally through either [VLLM](https://docs.litellm.ai/docs/providers/vllm) or [Ollama](https://docs.litellm.ai/docs/providers/ollama)
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You can run models locally through either [VLLM](https://docs.litellm.ai/docs/providers/vllm) or [Ollama](https://docs.litellm.ai/docs/providers/ollama)
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E.g. to use a new Hugging Face model locally via Ollama, set:
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E.g. to use a new model locally via Ollama, set in `.secrets.toml` or in a configuration file:
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```
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[__init__.py]
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MAX_TOKENS = {
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"model-name-on-ollama": <max_tokens>
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}
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e.g.
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MAX_TOKENS={
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...,
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"ollama/llama2": 4096
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}
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[config]
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model = "ollama/qwen2.5-coder:32b"
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fallback_models=["ollama/qwen2.5-coder:32b"]
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custom_model_max_tokens=128000 # set the maximal input tokens for the model
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duplicate_examples=true # will duplicate the examples in the prompt, to help the model to output structured output
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[config] # in configuration.toml
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model = "ollama/llama2"
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fallback_models=["ollama/llama2"]
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[ollama] # in .secrets.toml
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api_base = ... # the base url for your Hugging Face inference endpoint
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# e.g. if running Ollama locally, you may use:
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api_base = "http://localhost:11434/"
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[ollama]
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api_base = "http://localhost:11434" # or whatever port you're running Ollama on
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```
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### Inference Endpoints
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!!! note "Local models vs commercial models"
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Qodo Merge is compatible with almost any AI model, but analyzing complex code repositories and pull requests requires a model specifically optimized for code analysis.
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Commercial models such as GPT-4, Claude Sonnet, and Gemini have demonstrated robust capabilities in generating structured output for code analysis tasks with large input. In contrast, most open-source models currently available (as of January 2025) face challenges with these complex tasks.
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Based on our testing, local open-source models are suitable for experimentation and learning purposes, but they are not suitable for production-level code analysis tasks.
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Hence, for production workflows and real-world usage, we recommend using commercial models.
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### Hugging Face Inference Endpoints
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To use a new model with Hugging Face Inference Endpoints, for example, set:
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```
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[__init__.py]
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MAX_TOKENS = {
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"model-name-on-huggingface": <max_tokens>
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}
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e.g.
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MAX_TOKENS={
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...,
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"meta-llama/Llama-2-7b-chat-hf": 4096
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}
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[config] # in configuration.toml
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model = "huggingface/meta-llama/Llama-2-7b-chat-hf"
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fallback_models=["huggingface/meta-llama/Llama-2-7b-chat-hf"]
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custom_model_max_tokens=... # set the maximal input tokens for the model
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[huggingface] # in .secrets.toml
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key = ... # your Hugging Face api key
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@ -12,7 +12,6 @@ global_settings = Dynaconf(
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envvar_prefix=False,
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merge_enabled=True,
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settings_files=[join(current_dir, f) for f in [
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"settings/.secrets.toml",
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"settings/configuration.toml",
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"settings/ignore.toml",
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"settings/language_extensions.toml",
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@ -29,6 +28,7 @@ global_settings = Dynaconf(
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"settings/pr_add_docs.toml",
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"settings/custom_labels.toml",
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"settings/pr_help_prompts.toml",
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"settings/.secrets.toml",
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"settings_prod/.secrets.toml",
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]]
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)
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@ -34,6 +34,7 @@ ai_disclaimer_title="" # Pro feature, title for a collapsible disclaimer to AI
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ai_disclaimer="" # Pro feature, full text for the AI disclaimer
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output_relevant_configurations=false
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large_patch_policy = "clip" # "clip", "skip"
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duplicate_prompt_examples = false
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# seed
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seed=-1 # set positive value to fix the seed (and ensure temperature=0)
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temperature=0.2
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@ -125,6 +125,30 @@ The PR Diff:
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{{ diff_no_line_numbers|trim }}
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======
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{%- if duplicate_prompt_examples %}
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Example output:
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```yaml
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code_suggestions:
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- relevant_file: |
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src/file1.py
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language: |
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python
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suggestion_content: |
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...
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existing_code: |
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...
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improved_code: |
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...
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one_sentence_summary: |
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...
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label: |
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...
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```
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(replace '...' with actual content)
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{%- endif %}
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Response (should be a valid YAML, and nothing else):
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```yaml
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@ -122,6 +122,25 @@ Below are {{ num_code_suggestions }} AI-generated code suggestions for enhancing
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======
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{%- if duplicate_prompt_examples %}
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Example output:
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```yaml
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code_suggestions:
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- suggestion_summary: |
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...
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relevant_file: "..."
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relevant_lines_start: ...
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relevant_lines_end: ...
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suggestion_score: ...
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why: |
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...
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- ...
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```
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(replace '...' with actual content)
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{%- endif %}
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Response (should be a valid YAML, and nothing else):
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```yaml
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"""
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@ -130,6 +130,37 @@ The PR Git Diff:
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Note that lines in the diff body are prefixed with a symbol that represents the type of change: '-' for deletions, '+' for additions, and ' ' (a space) for unchanged lines.
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{%- if duplicate_prompt_examples %}
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Example output:
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```yaml
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type:
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- Bug fix
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- Refactoring
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- ...
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description: |
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...
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title: |
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...
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{%- if enable_semantic_files_types %}
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pr_files:
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- filename: |
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...
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{%- if include_file_summary_changes %}
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changes_summary: |
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...
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{%- endif %}
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changes_title: |
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...
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label: |
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label_key_1
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...
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{%- endif %}
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```
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(replace '...' with the actual values)
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{%- endif %}
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Response (should be a valid YAML, and nothing else):
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```yaml
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@ -221,6 +221,59 @@ The PR code diff:
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======
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{%- if duplicate_prompt_examples %}
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Example output:
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```yaml
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review:
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{%- if related_tickets %}
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ticket_compliance_check:
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- ticket_url: |
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...
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ticket_requirements: |
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...
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fully_compliant_requirements: |
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...
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not_compliant_requirements: |
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...
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overall_compliance_level: |
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...
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{%- endif %}
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{%- if require_estimate_effort_to_review %}
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estimated_effort_to_review_[1-5]: |
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3
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{%- endif %}
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{%- if require_score %}
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score: 89
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{%- endif %}
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relevant_tests: |
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No
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key_issues_to_review:
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- relevant_file: |
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...
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issue_header: |
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...
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issue_content: |
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...
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start_line: ...
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end_line: ...
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- ...
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security_concerns: |
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No
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{%- if require_can_be_split_review %}
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can_be_split:
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- relevant_files:
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- ...
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- ...
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title: ...
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- ...
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{%- endif %}
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```
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(replace '...' with the actual values)
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{%- endif %}
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Response (should be a valid YAML, and nothing else):
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```yaml
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"""
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@ -81,6 +81,7 @@ class PRCodeSuggestions:
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"relevant_best_practices": "",
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"is_ai_metadata": get_settings().get("config.enable_ai_metadata", False),
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"focus_only_on_problems": get_settings().get("pr_code_suggestions.focus_only_on_problems", False),
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'duplicate_prompt_examples': get_settings().config.get('duplicate_prompt_examples', False),
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}
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self.pr_code_suggestions_prompt_system = get_settings().pr_code_suggestions_prompt.system
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@ -830,7 +831,8 @@ class PRCodeSuggestions:
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"diff": patches_diff,
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'num_code_suggestions': len(suggestion_list),
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'prev_suggestions_str': prev_suggestions_str,
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"is_ai_metadata": get_settings().get("config.enable_ai_metadata", False)}
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"is_ai_metadata": get_settings().get("config.enable_ai_metadata", False),
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'duplicate_prompt_examples': get_settings().config.get('duplicate_prompt_examples', False)}
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environment = Environment(undefined=StrictUndefined)
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if dedicated_prompt:
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@ -71,7 +71,8 @@ class PRDescription:
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"custom_labels_class": "", # will be filled if necessary in 'set_custom_labels' function
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"enable_semantic_files_types": get_settings().pr_description.enable_semantic_files_types,
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"related_tickets": "",
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"include_file_summary_changes": len(self.git_provider.get_diff_files()) <= self.COLLAPSIBLE_FILE_LIST_THRESHOLD
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"include_file_summary_changes": len(self.git_provider.get_diff_files()) <= self.COLLAPSIBLE_FILE_LIST_THRESHOLD,
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'duplicate_prompt_examples': get_settings().config.get('duplicate_prompt_examples', False),
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}
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self.user_description = self.git_provider.get_user_description()
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@ -94,6 +94,7 @@ class PRReviewer:
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"enable_custom_labels": get_settings().config.enable_custom_labels,
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"is_ai_metadata": get_settings().get("config.enable_ai_metadata", False),
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"related_tickets": get_settings().get('related_tickets', []),
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'duplicate_prompt_examples': get_settings().config.get('duplicate_prompt_examples', False),
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}
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self.token_handler = TokenHandler(
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Reference in New Issue
Block a user